Abstract: Breast cancer is reported to be the most common cancer type among women worldwide and it is the second highest women fatality rate amongst all cancer types. Notwithstanding all the progresses made in prevention and early intervention, early prognosis and survival prediction rates are still not sufficient. In this paper, we propose an ANN model which outperforms all the previous supervised learning methods by reaching 99.57 in terms of accuracy in Wisconsin Breast Cancer (...) dataset. Experimental results on Haberman’s Breast Cancer Survival dataset show the superiority of proposed method by reaching 88.24 % in terms of accuracy. The results are the best reported ones obtained from Artificial Neural Network using JNN environment without any preprocessing of the dataset. (shrink)

The Knowledge Based System for Diagnosing Breast Cancer is used to assist medical students to improve their education on diagnosis and counseling the process of analyzing the biopsy image of the microscope, determining the type of tumor and the treatment method for each case and identifying the disease related questions. According to the Ministry of Health in its annual report in Gaza, between 2009 and 2014 there are 7069 cases of breast cancer, and in 2014 there (...) are 1502 cases of breast cancer . We are now in the age of visual information where 65% of the populations are visual learners; the Knowledge Based System is the easiest way to ensure students remember the information in the long term, using visual and textual information. The Knowledge Based System has an easy-to-use interface to help students diagnose the disease and enhance their information about the disease; the system can be used on smart phones. This Knowledge Based System can be divided into three main parts: The first part is specific questions for the patient, to help student to know questions type. The second part is the process of analyzing the biopsy sample image, to see if the biopsy image is intact or infected. The last part is the video shows ways to treat breast cancer in the form of animation. (shrink)

Breast cancer remains a significant health concern worldwide, necessitating the development of effective diagnostic tools. In this study, we employ a neural network-based approach to analyze the Wisconsin Breast Cancer dataset, sourced from Kaggle, comprising 570 samples and 30 features. Our proposed model features six layers (1 input, 1 hidden, 1 output), and through rigorous training and validation, we achieve a remarkable accuracy rate of 99.57% and an average error of 0.000170 as shown in the image (...) below. Furthermore, our investigation identifies the most influential features in breast cancer diagnosis, shedding light on the key determinants of malignancy. Notably, we find that factors such as fractal dimension_se, symmetry worst, compactness_worst, symmetry_se, and smoothness_se play pivotal roles in distinguishing between benign and malignant cases. This research contributes to the ongoing efforts to enhance breast cancer diagnosis, providing valuable insights into feature importance and showcasing the potential of neural networks in medical applications. Our findings have implications for improving early detection and treatment strategies, ultimately contributing to improved patient outcomes. (shrink)

The “Expert System for Diagnosing Breast Cancer" is used to assist medical students to improve their education on diagnosis and counseling the process of analyzing the biopsy image of the microscope, determining the type of tumor and the treatment method for each case and identifying the disease related questions. According to the Ministry of Health in its annual report in Gaza, between 2009 and 2014 there are 7069 cases of breast cancer, and in 2014 there are (...) 1502 cases of breast cancer . We are now in the age of visual information where 65% of the populations are visual learners; the expert system is the easiest way to ensure students remember the information in the long term, using visual and textual information. The expert system has an easy-to-use interface to help students diagnose the disease and enhance their information about the disease; the system can be used on smart phones. This expert system can be divided into three main parts: The first part is specific questions for the patient, to help student to know questions type. The second part is the process of analyzing the biopsy sample image, to see if the biopsy image is intact or infected. The last part is the video shows ways to treat breast cancer in the form of animation. (shrink)

Abstract—Breast cancer is considered the second most common cancer in women compared to all other cancers. It is fatal in less than half of all cases and is the main cause of mortality in women. It accounts for 16% of all cancer mortalities worldwide. Early diagnosis of breast cancer increases the chance of recovery. Data mining techniques can be utilized in the early diagnosis of breast cancer. In this paper, an academic experimental (...) breast cancer dataset is used to perform a data mining practical experiment using the Waikato Environment for Knowledge Analysis (WEKA) tool. The WEKA Java application represents a rich resource for conducting performance metrics during the execution of experiments. Pre-processing and feature extraction are used to optimize the data. The classification process used in this study was summarized through thirteen experiments. Additionally, 10 experiments using various different classification algorithms were conducted. The introduced algorithms were: Naïve Bayes, Logistic Regression, Lazy IBK (Instance-Bases learning with parameter K), Lazy Kstar, Lazy Locally Weighted Learner, Rules ZeroR, Decision Stump, Decision Trees J48, Random Forest and Random Trees. The process of producing a predictive model was automated with the use of classification accuracy. Further, several experiments on classification of Wisconsin Diagnostic Breast Cancer and Wisconsin Breast Cancer, were conducted to compare the success rates of the different methods. Results conclude that Lazy IBK classifier k-NN can achieve 98% accuracy among other classifiers. The main advantages of the study were the compactness of using 13 different data mining models and 10 different performance measurements, and plotting figures of classifications errors. (shrink)

Objective: The use of neoadjuvant chemotherapy (NACT) in breast cancer is increasing. The management of locally advanced breast cancer differs due to the approach of the center to which the patient applied and the approach of the following physician. From this point of view, we aimed to evaluate the real life data of our region. -/- Methods: The study included 106 patients treated with neoadjuvant chemotherapy in the medical oncology clinic of two different university hospitals. Association (...) between clinicopathological features and pathological complete response (pCR) were analyzed. -/- Results: The pCR rate was higher in patients with negative hormone receptors and this difference was statistically significant (p:0.000). The rate of obtaining pCR increased as the NACT duration increased, and this increase was statistically significant. The mean NACT duration applied to the patients with pCR was 5.48 ± 0.22 months, and the mean NACT duration for those who could not obtain pCR was 5.01 ± 0.1 months (p:0.041). The recurrence rate of patients with pCR was 11.1%, while the recurrence rate of patients who could not obtain pCR was 31.6% (p:0.04). -/- Conclusions: Pathological response to chemotherapy is an important factor in determining prognosis. There appears to be a need for new biomarkers that allow the prediction of pCR and long-term outcomes. (shrink)

Breast cancer is the leading cause of death among women with cancer. Computer-aided diagnosis is an efficient method for assisting medical experts in early diagnosis, improving the chance of recovery. Employing artificial intelligence (AI) in the medical area is very crucial due to the sensitivity of this field. This means that the low accuracy of the classification methods used for cancer detection is a critical issue. This problem is accentuated when it comes to blurry mammogram images. (...) In this paper, convolutional neural networks (CNNs) are employed to present the traditional convolutional neural network (TCNN) and supported convolutional neural network (SCNN) approaches. The TCNN and SCNN approaches contribute by overcoming the shift and scaling problems included in blurry mammogram images. In addition, the flipped rotation-based approach (FRbA) is proposed to enhance the accuracy of the prediction process (classification of the type of cancerous mass) by taking into account the different directions of the cancerous mass to extract effective features to form the map of the tumour. The proposed approaches are implemented on the MIAS medical dataset using 200 mammogram breast images. Compared to similar approaches based on KNN and RF, the proposed approaches show better performance in terms of accuracy, sensitivity, spasticity, precision, recall, time of performance, and quality of image metrics. (shrink)

Iniaalok ng pag-aaral na ito ang isang panunuring Foucauldian sa pangkasariang karanasan ng babaeng may breast cancer (BRCA). Inihahain din ng mga may-akda ang mga sumusunod na tanong: Paano naaapi ang babaeng may BRCA? Paano hinahamon ng kanyang karanasan ang konsepto ng seksuwalidad? Maaari bang ituring ang kanyang karanasan bilang anyo ng pagbalikwas? Tutugunan ng mga may-akda ang naturang mga tanong gamit ang kapangyarihan-diskurso-seksuwalidad ni Foucault habang ipinapalagay na: (1) matagumpay na naipapakita ng talaangkanan ng seksuwalidad ni Foucault (...) kung paanong ang seksuwalidad, bilang isang diskursibong kontrak, ay ginagamit bilang isang teknik ng pangongontrol, at (2) nabibigyan tayo ni Foucault ng isang paraan ng pag-unawa sa kung papaano tumutugon ang indibidwal sa iba’t ibang sistema ng kontrol, maging ng isang balangkas na makapagpapaliwanag sa maraming relasyong pangkapangyarihan na siyang tumutukoy sa moda ng pag-iral ng indibidwal. Nahahati ang papel na ito sa tatlong pangunahing bahagi: (1) Ang Panunuring Feminista ng Sabjek na Foucauldian, (2) Ang Pangkasariang Karanasan ng Babaeng may BRCA, at (3) Pagbalikwas bilang Diskurso-Konstrak at Binuong Tugon. (shrink)

Over the past year, technology companies have made headlines claiming that their artificially intelligent (AI) products can outperform clinicians at diagnosing breast cancer, brain tumours, and diabetic retinopathy. Claims such as these have influenced policy makers, and AI now forms a key component of the national health strategies in England, the United States, and China. While it is positive to see healthcare systems embracing data analytics and machine learning, concerns remain about the efficacy, ethics, and safety of some (...) commercial, AI health solutions. This paper argues that improved regulation and guidance is urgently required to mitigate risks, ensure transparency and best practice, Without this, patients, clinicians, and other stakeholders cannot be assured of an app’s efficacy, and safety. (shrink)

Objective: In this study, we aimed to identify patients at risk of chemotherapy-induced cardiotoxicity with a simple method like platelet-to-lymphocyte ratio (PLR) before starting therapy. Method: A total of 65 breast cancer patients who completed anthracycline or adjuvant trastuzumab treatment were evaluated retrospectively. Serial PLR calculations, echocardiographic examinations, and cardiac markers before treatment and after follow-up period were analyzed. Cardiotoxicity was determined according to Cardiac Review and Evaluation Committee Criteria. Results: Patients were divided into two groups according to (...) their baseline PLR levels as Group C—PLR < 119 and Group D—PLR 120. The median follow-up of the study was 22.23 (12-42) months. Concomitant disease and baseline characteristics were similar in both groups. Symptomatic cardiotoxicity was not observed in both groups. Cardiotoxicity was occurred in one patient (2.3%) in Group C and in four patients (9.5%) in Group D (P ¼ .005). Average mean left ventricular ejection fraction loss from baseline was 10.7 6 7.0% in Group D vs 2.3 6 6.4% in Group C (P ¼ .008). Interpretation of cardiac markers that were present in nearly half of the patients revealed that serum hs-c-reactive protein and pro-brain natriu¨ retic peptide levels were significantly higher in patients who developed cardiotoxicity compared to who did not develop cardiotoxicity. PLR 120 had 99% sensitivity and 85% specificity in predicting cardiotoxicity. Conclusion: This study’s results showed that high PLR levels were associated with chemotherapy-induced cardiotoxicity. To our best knowledge, this is the first study, examining the impact of whole blood test on chemotherapy-induced cardiotoxicity before starting the therapy and allowing doctors plot a route for these risky patients. (shrink)

In accordance with the critical women’s health literature recounting the ways that women are encouraged to submit themselves to various sorts of health “imperatives”, I investigate the messages tacitly conveyed to women in “campaigns for the cure” and breast cancer awareness efforts, which, I argue, overemphasizes a “positive attitude”, healthy lifestyle, and cure rather than prevention of this life-threatening disease. I challenge that the message of hope pervading breast cancer discourse silences the despair felt by many (...) women, furthers a tacit blaming for disease infliction via a rhetoric of personal responsibility, underemphasizes other cogent health determinants like environmental toxicity, and undermines legitimate critiques of current biomedical practices like widespread mammography. While finding a cure for breast cancer is a laudable and worthwhile healthcare goal that can understandably be shared by women’s health activists, corporate sponsors, and the medical community, this paper resists the current formation of campaigns for the cure and “pink ribbon activism” in general. (shrink)

Breast cancer treatment is being transformed by artificial intelligence (AI). Nevertheless, most scientists, engineers, and physicians aren't ready to contribute to the healthcare AI revolution. In this paper, we discuss our experiences teaching a new American student undergraduate course that seeks to train the next generation for cross-cultural design thinking, which we believe is critical for AI to realize its full potential in breast cancer treatment. The main tasks of this course are preparing, performing and translating (...) interviews with healthcare professionals from both Portugal and the USA. Since the course is offered in Portugal as a short-term faculty-led study abroad program, students can explore the effect of culture on healthcare delivery and the design of healthcare technologies. The learning tests demonstrated student growth for breast cancer treatment in many areas important for the development of AI. In respect to understanding breast cancer care, most students had undervalued the effect of cancer and its treatment on the quality of life of women before taking this course and most were unaware of the importance of multidisciplinary care teams. Regarding AI in medical, students became more mindful of data privacy issues and the need to consider the effect of AI on healthcare professionals. (shrink)

Ongoing research in the fields of genetics and biotechnology hold the promise of improved diagnosis and treatment of genetic diseases, and potentially the development of individually tailored pharmaceuticals and gene therapies. Difficulty, however, arises in determining how these services are to be evaluated and integrated equitably into public health care systems such as Canada's. The current context is one of increasing fiscal restraint on the part of governments, limited financial resources being dedicated to health care, and rising costs for new (...) health care services and technologies. This has led to increasing public debate in the last few years about how to reform public health care, and whether we should prohibit, permit or perhaps even encourage private purchase of health care services. ;In Canada, some of these concerns have crystallized around the issue of gene patents and commercial genetic testing, in particular as illustrated by the case of Myriad Genetics' patented BRACAnalysis test for hereditary breast and ovarian cancer. While most Canadians who currently access genetic services do so through the public health care system, for those with the means, private purchase is becoming an option. This situation raises serious concerns---about justice in access to health care; about continued access to safe and reliable genetic testing supported by unbiased patient information; and about the broader effects of commercialization for ongoing research and the Canadian public health care system. Commercial genetic testing presents a challenge to health care professionals, policy analysts, and academics concerned with the social, ethical and policy implications of new genetic technologies. Using the Myriad case as an exemplar, tools from moral philosophy, the social sciences, and health policy and law will be brought to bear on the larger issues of how as a society we should regulate commercial research and product development, and more coherently decide which services to cover under public health insurance and which to leave to private purchase. Generally, the thesis is concerned with the question of "how best to bring capital, morality, and knowledge into a productive and ethical relationship". (shrink)

Interoperability across data sets is a key challenge for quantitative histopathological imaging. There is a need for an ontology that can support effective merging of pathological image data with associated clinical and demographic data. To foster organized, cross-disciplinary, information-driven collaborations in the pathological imaging field, we propose to develop an ontology to represent imaging data and methods used in pathological imaging and analysis, and call it Quantitative Histopathological Imaging Ontology – QHIO. We apply QHIO to breast cancer hot-spot (...) detection with the goal of enhancing reliability of detection by promoting the sharing of data between image analysts. (shrink)

Policy-makers must sometimes choose between an alternative which has somewhat lower expected value for each person, but which will substantially improve the outcomes of the worst off, or an alternative which has somewhat higher expected value for each person, but which will leave those who end up worst off substantially less well off. The popular ex ante Pareto principle requires the choice of the alternative with higher expected utility for each. We argue that ex ante Pareto ought to be rejected (...) because it conflicts with the requirement that, when possible, one ought to decide as one would with full information. We apply our argument in an analysis of US policy on screening for breast cancer. -/- . (shrink)

This fifth volume on Advances and Applications of DSmT for Information Fusion collects theoretical and applied contributions of researchers working in different fields of applications and in mathematics, and is available in open-access. The collected contributions of this volume have either been published or presented after disseminating the fourth volume in 2015 in international conferences, seminars, workshops and journals, or they are new. The contributions of each part of this volume are chronologically ordered. First Part of this book presents some (...) theoretical advances on DSmT, dealing mainly with modified Proportional Conflict Redistribution Rules (PCR) of combination with degree of intersection, coarsening techniques, interval calculus for PCR thanks to set inversion via interval analysis (SIVIA), rough set classifiers, canonical decomposition of dichotomous belief functions, fast PCR fusion, fast inter-criteria analysis with PCR, and improved PCR5 and PCR6 rules preserving the (quasi-)neutrality of (quasi-)vacuous belief assignment in the fusion of sources of evidence with their Matlab codes. Because more applications of DSmT have emerged in the past years since the apparition of the fourth book of DSmT in 2015, the second part of this volume is about selected applications of DSmT mainly in building change detection, object recognition, quality of data association in tracking, perception in robotics, risk assessment for torrent protection and multi-criteria decision-making, multi-modal image fusion, coarsening techniques, recommender system, levee characterization and assessment, human heading perception, trust assessment, robotics, biometrics, failure detection, GPS systems, inter-criteria analysis, group decision, human activity recognition, storm prediction, data association for autonomous vehicles, identification of maritime vessels, fusion of support vector machines (SVM), Silx-Furtif RUST code library for information fusion including PCR rules, and network for ship classification. Finally, the third part presents interesting contributions related to belief functions in general published or presented along the years since 2015. These contributions are related with decision-making under uncertainty, belief approximations, probability transformations, new distances between belief functions, non-classical multi-criteria decision-making problems with belief functions, generalization of Bayes theorem, image processing, data association, entropy and cross-entropy measures, fuzzy evidence numbers, negator of belief mass, human activity recognition, information fusion for breast cancer therapy, imbalanced data classification, and hybrid techniques mixing deep learning with belief functions as well. (shrink)

Utilitarianism, it has been said, is not sensitive to the distribution of welfare. In making risky decisions for others there are multiple sensitivities at work. I present examples of risky decision-making involving drug allocations, charitable giving, breast-cancer screening and C-sections. In each of these examples there is a different sensitivity at work that pulls away from the utilitarian prescription. Instances of saving fewer people at a greater risk to many is more complex because there are two distributional sensitivities (...) at work that pull in opposite directions from the utilitarian calculus. I discuss objections to these sensitivities and conclude with some reflections on the value of formal modelling in thinking about societal risk. (shrink)

Abstract: The present review encompasses the contraception, methods of contraception, hormonal or chemical birth control pills and the herbal products having contraceptive activity with their merits and demerits. The commercially available birth control pills are detrimental to women health, might be life-threatening sometimes. The detrimental effects posed by such pills are: fat deposition in the liver, kidney and uterus, prevention of metabolism and further conception, disruption of the epithelial layer of the uterus, irregular and painful menstruation, breast cancer (...) and ultimately permanent infertility. This study will help us to view the undeniable baleful effects of the commercial birth control pills and thus will rush us to explore some herbal birth control pills that will be cheaper, having no side effects and might be effective for the sexes (male & female). A research work has already been conducted in this regard which might be an evolutionary step in this realm. (shrink)

I argue that ductal carcinoma in situ (DCIS), the tumor most commonly diagnosed by breast mammography, cannot be confidently classified as cancer, that is, as pathological. This is because there may not be dysfunction present in DCIS—as I argue based on its high prevalence and the small amount of risk it conveys—and thus DCIS may not count as a disease by dysfunction-requiring approaches, such as Boorse’s biostatistical theory and Wakefield’s harmful dysfunction account. Patients should decide about treatment for (...) DCIS based on the risks it poses and the risks and benefits of treatment, not on its disease status. (shrink)

Background: Obstetrics and gynaecology are many and common, where a woman suffers from problems related to pregnancy or her reproductive organs. Any part of her body may be affected due to some symptoms that are completely related to the reproductive organs when she is in a critical period for her, whether in her menstrual cycle, pregnancy, or disease conditions. The bulk of cases of diseases related to women and childbirth are dealt with great care and special care, as all diseases (...) related to women are considered very sensitive diseases due to the presence of the disease in sensitive and not simple places. A gynaecologist is a specialist in all diseases and problems related to the female sexual organs. They perform regular preventive medical exams, such as cervical smear tests and breast exams. It also provides consultations for women of all ages about the problems of contraception, infertility and menopause. Objectives: The objective of this expert system is to help and facilitate women in diagnosing diseases related to their obstetrics and gynaecology, a simple expert system has been designed consisting of ten various common diseases that affect women whether During or without pregnancy, Methods: In this system, the system consists of a list of some common symptoms, the correct diagnosis adopted for these diseases, and how to treat diseases in the correct way with the help of a consultant obstetrician and gynaecologist, Dr. Fathi Muhammad Al-Habibi, and these diseases are: uterine cancer, cervical cancer, Infertility, double uterus, ectopic pregnancy, endometrial cancer, female sexual dysfunction, endometriosis, faecal incontinence, female infertility, CLIPS Expert System language was used to design and implement the proposed expert system. Results: The proposed ten obstetrics and gynaecology diagnostic expert system was evaluated by medical students and they were satisfied with its performance. Conclusions: The proposed expert system is very useful for obstetricians and gynaecologists, patients with reproductive system problems, and recent graduates. (shrink)

Current debate and policy surrounding the use of genetic editing in humans often relies on a binary distinction between therapy and human enhancement. In this paper, we argue that this dichotomy fails to take into account perhaps the most significant potential uses of CRISPR-Cas9 gene editing in humans. We argue that genetic treatment of sporadic Alzheimer’s disease, breast- and ovarian-cancer causing BRCA1/2 mutations and the introduction of HIV resistance in humans should be considered within a new category of (...) genetic protection treatments. We find that if this category is not introduced, life-altering research might be unnecessarily limited by current or future policy. Otherwise ad hoc decisions might be made, which introduce a risk of unforeseen moral costs, and might overlook or fail to address some important opportunities. (shrink)

The aim of this paper is to assess the relevance of somatic evolution by natural selection to our understanding of cancer development. I do so in two steps. In the first part of the paper, I ask to what extent cancer cells meet the formal requirements for evolution by natural selection, relying on Godfrey-Smith’s (2009) framework of Darwinian populations. I argue that although they meet the minimal requirements for natural selection, cancer cells are not paradigmatic Darwinian populations. (...) In the second part of the paper, I examine the most important examples of adaptation in cancer cells. I argue that they are not significant accumulations of evolutionary changes, and that as a consequence natural selection plays a lesser role in their explanation. Their explanation, I argue, is best sought in the previously existing wiring of the healthy cells. (shrink)

In this paper, we developed an Artificial Neural Network (ANN) for detect the absence or presence of lung cancer in human body. Symptoms were used to diagnose the lung cancer, these symptoms such as Yellow fingers, Anxiety, Chronic Disease, Fatigue, Allergy, Wheezing, Coughing, Shortness of Breath, Swallowing Difficulty and Chest pain. They were used and other information about the person as input variables for our ANN. Our ANN established, trained, and validated using data set, which its title is (...) “survey lung cancer”. Model evaluation showed that the ANN model is able to detect the absence or presence of lung cancer with 96.67 % accuracy. (shrink)

Cancer research is experiencing ‘paradigm instability’, since there are two rival theories of carcinogenesis which confront themselves, namely the somatic mutation theory and the tissue organization field theory. Despite this theoretical uncertainty, a huge quantity of data is available thanks to the improvement of genome sequencing techniques. Some authors think that the development of new statistical tools will be able to overcome the lack of a shared theoretical perspective on cancer by amalgamating as many data as possible. We (...) think instead that a deeper understanding of cancer can be achieved by means of more theoretical work, rather than by merely accumulating more data. To support our thesis, we introduce the analytic view of theory development, which rests on the concept of plausibility, and make clear in what sense plausibility and probability are distinct concepts. Then, the concept of plausibility is used to point out the ineliminable role played by the epistemic subject in the development of statistical tools and in the process of theory assessment. We then move to address a central issue in cancer research, namely the relevance of computational tools developed by bioinformaticists to detect driver mutations in the debate between the two main rival theories of carcinogenesis. Finally, we briefly extend our considerations on the role that plausibility plays in evidence amalgamation from cancer research to the more general issue of the divergences between frequentists and Bayesians in the philosophy of medicine and statistics. We argue that taking into account plausibility-based considerations can lead to clarify some epistemological shortcomings that afflict both these perspectives. (shrink)

Cancer biology features the ascription of normal functions to parts of cancers. At least some ascriptions of function in cancer biology track local normality of parts within the global abnormality of the aberration to which those parts belong. That is, cancer biologists identify as functions activities that, in some sense, parts of cancers are supposed to perform, despite cancers themselves having no purpose. The present paper provides a theory to accommodate these normal function ascriptions—I call it the (...) Modeling Account of Normal Function (MA). MA comprises two claims. First, normal functions are activities whose performance by the function-bearing part contributes to the self-maintenance of the whole system and, thereby, results in the continued presence of that part. Second, MA holds that models of system-level activities that are (partly) constitutive of self-maintenance are improved by including a representation of the relevant function-bearing part and by making reference to the activity/activities that part performs which contribute(s) to those system-level activities. I contrast MA with two other accounts that seek to explicate the ascription of normal functions in biology, namely, the organizational account and the selected effects account. Both struggle to extend to cancer biology. However, I offer ecumenical readings which allow them to recover some ascriptions of normal function to parts of cancers. So, though I contend that MA excels in this respect, the purpose of this paper is served if it provides materials for bridging the gap between cancer biology, philosophy of cancer, and the literature on function. (shrink)

The problem of cancer is examined from the metaphysical standpoint of essence and ground. An essentialist definition of cancer is assumed that would be valid in all possible worlds in which cancer could logically exist. The grounds of cancer are then examined and elucidated. Two grounding cancer properties are identified and discussed: symmetry- breaking and computational intelligence. Each examination leads to concrete conclusions for novel therapeutic approaches and a more fundamental understanding of what cancer (...) is at bottom. Other possible cancer grounding properties related to evolution, adaptability and stochastic features are identified for future work. This approach is novel and offers new solutions to the problem of cancer. (shrink)

In liberal moral theory, interfering with someone’s deliberate engagement in a self-harming practice in order to promote their own good is often considered wrongfully paternalistic. But what if self-harming decisions are the product of an oppressive social context that imposes harmful norms on certain individuals, such as, arguably, in the case of cosmetic breast surgery? Clare Chambers suggests that such scenarios can mandate state interference in the form of prohibition. I argue that, unlike conventional measures, Chambers’ proposal recognises that (...) harmful, discriminatory norms entail a twofold collective moral obligation: to eliminate the harmful norm in the long run, but also to address unjust harm that is inflicted in the meantime. I show that these two obligations tend to pull in opposite directions, thus generating a serious tension in Chambers’ proposal which eventually leads to an undue compromising of the second obligation in favour of the first. Based on this discussion, I develop an alternative proposal which, instead of prohibiting breast implant surgery, offers compensation for the disadvantages suffered by individuals who decide not to have surgery. (shrink)

Cancer care has transitioned from clinical-based to home-based care to support longterm care in a more familiar and comfortable environment. This care transition has put family caregivers (FCGs) in a strategic position as care providers. Cancer care at home involves psychological and emotional treatment at some point, making FCGs deal with the stress of cancer patients frequently. Due to their limited care competencies, they need supportive care from healthcare professionals in cancer stress management. This study aims (...) to examine how types of demanded healthcare information affect the FCG’s role in reducing the stress of female cancer patients. The mindsponge theory was used in conceptual development and interpretation. Bayesian Mindsponge Framework (BMF) analytics were used for statistical analysis on a dataset of 48 spouses (husbands) and 12 other family members in five congested communities of Surabaya, Indonesia. Results showed that among the six types of healthcare information, FCGs with higher demand for cancer-specific information were more likely to need support in reducing the stress of female cancer patients. Meanwhile, FCGs with a higher demand for information about support services were less likely to need support to reduce cancer patients’ stress. Other types of healthcare information have ambiguous effects on the need for support in reducing cancer-induced stress. This study reveals that the demanded cancer-specific information, e.g., cancer prognosis or likely outcome, must be prioritized to assist FCG’s role in managing cancer stress. (shrink)

Although there is a growing recognition that older adults and those with extensive comorbid conditions undergo cancer screening too frequently, there is little information about patients’ perceptions regarding cessation of cancer screening. Information on older adults’ views of screening cessation would be helpful both for clinicians and for those designing interventions to reduce overscreening.

Adaptation and stress are two main concepts useful for better understanding the phases of illness and health-related human behavior. The two faces of adaptation, adaptation as a process and adaptation as a product, have raised the question of how long the adaptation process will take in cancer trajectories. The care setting transition from clinical-based into home-based cancer care has stressed the role of family caregivers (FCG) in cancer management. This study examines how types of demanded healthcare information (...) affect the FCG’s role in catalyzing the adaptation of female cancer patients. The mindsponge theory was used in conceptual development and results interpretation. Bayesian Mindsponge Framework (BMF) analytics was used for statistical analysis on a dataset of 48 spouses (husbands) and 12 other family members in five congested communities of Surabaya, Indonesia. Results showed that among the six types of demanded healthcare information, FCGs with a higher tendency to demand cancer-specific information are more likely to need support in catalyzing the adaptation of female cancer patients. Meanwhile, FCGs with a higher demand for information on alternative therapies are less likely to need support in catalyzing cancer adaptation. Other types of healthcare information have ambiguous effects on the need for support in cancer adaptation assistance. This study reveals that the demanded cancer-specific information, e.g., cancer’s prognosis or likely outcome, must be prioritized to assist FCG’s role in catalyzing adaptation among female cancer patients. Cancer prognosis and outcomes reflect the future of cancer care results. (shrink)

Cancer biologists ascribe normal functions to parts of cancer. Normal functions are activities that parts of systems are in some minimal sense supposed to perform. Cancer biologists’ finding normality within the abnormality of cancer pose difficulties for two main approaches to normal function. One approach claims that normal functions are activities that parts are selected for. However, some parts of cancers that have normal functions aren’t selected to perform them. The other approach claims that normal functions (...) are part-activities typical for the system and that contribute to survival/reproduction. However, cancers are too heterogeneous to establish what’s typical across a type. (shrink)

Fear of cancer is mostly related to cancer recurrence, metastasis, additional cancer, and diagnostic tests. Its legacy as a lethal disease has raised fear of approaching death. Currently, cancer’s total suffering and the worsening phenomena have raised fear, especially among female patients. Family caregivers (FCGs) who are responsible for the day-to-day cancer care at home need to help the patients deal with this fear frequently. Due to the limited care competencies, they need supportive care from (...) healthcare professionals in cancer fear management. This study aims to assess how types of demanded healthcare information affect the FCG’s role in reducing the fear of female cancer patients. The mindsponge theory was used in conceptual development and interpretation. Bayesian Mindsponge Framework (BMF) analytics were used for statistical analysis on a dataset of 48 spouses (husbands) and 12 other family members in five congested communities of Surabaya, Indonesia. Results showed that among the six types of healthcare information, FCGs with higher demand on cancer-specific information and information on cancer physical needs were more likely to need support in reducing the fear of female cancer patients. Meanwhile, FCGs with a higher demand for information on support services were less likely to need support to reduce cancer patients’ fear. Other types of healthcare information have ambiguous effects on the need for support in reducing cancer-induced fear. This study reveals that the demanded cancer-specific information, e.g., cancer’s prognosis or likely outcome and information on cancer physical needs, need to be met in priority to assist FCG’s role in cancer fear management. (shrink)

This chapter considers ethical issues involved in genetic testing and screening for susceptibility to various forms of cancer.

Many researchers consider cancer to have molecular causes, namely mutated genes that result in abnormal cell proliferation (e.g. Weinberg 1998). For others, the causes of cancer are to be found not at the molecular level but at the tissue level where carcinogenesis consists of disrupted tissue organization with downward causation effects on cells and cellular components (e.g. Sonnenschein and Soto 2008). In this contribution, I ponder how to make sense of such downward causation claims. Adopting a manipulationist account (...) of causation (Woodward 2003), I propose a formal definition of downward causation and discuss further requirements (in light of Baumgartner 2009). I then show that such an account cannot be mobilized in support of non-reductive physicalism (contrary to Raatikainen 2010). However, I also argue that such downward causation claims might point at particularly interesting dynamic properties of causal relationships that might prove salient in characterizing causal relationships (following Woodward 2010). (shrink)

Many researchers consider cancer to have molecular causes, namely mutated genes that result in abnormal cell proliferation (e.g. Weinberg 1998); yet for others, the causes of cancer are to be found not at the molecular level but at the tissue level and carcinogenesis would consist in a disrupted tissue organization with downward causation effects on cells and cellular components (e.g. Sonnenschein & Soto 2008). In this contribution, I ponder how to make sense of such downward causation claims. Adopting (...) a manipulationist account of causation (Woodward 2003), I propose a formal definition of downward causation, and discuss further requirements (in light of Baumgartner 2009). I then show that such an account cannot be mobilized in support of non-reductive physicalism (contrary to Raatikainen 2010). However, I also argue that such downward causation claims might point at particularly interesting dynamic properties of causal relationships that might prove salient in characterizing causal relationships (following Woodward 2010). (shrink)

To emphasize what we have outlined in a preceding paper, we consider the following: that human consciousness model should take into consideration “spirit” role, i.e. the mind-body-spirit as integral aspect, which view is neglected in the so-called Freudian mental model. In this paper, we consider two approaches to cancer treatment derived from such an integral triune view of human consciousness, including (a) healing frequency approach as advised by Royal Rife and David Hawkins, and also (b) relational therapy, based on (...) recent research on the healing role of love and compassion. (shrink)

In this paper, we developed an Artificial Neural Network (ANN) for detect the absence or presence of lung cancer in human body. Symptoms were used to diagnose the lung cancer, these symptoms such as Yellow fingers, Anxiety, Chronic Disease, Fatigue, Allergy, Wheezing, Coughing, Shortness of Breath, Swallowing Difficulty and Chest pain. They were used and other information about the person as input variables for our ANN. Our ANN established, trained, and validated using data set, which its title is (...) “survey lung cancer”. Model evaluation showed that the ANN model is able to detect the absence or presence of lung cancer with 96.67 % accuracy. -/- . (shrink)

Lung cancer is a serious and deadly disease that affects the lungs, which are responsible for taking in oxygen and expelling carbon dioxide from the body. The disease can develop in any part of the lungs and is usually caused by smoking or exposure to certain chemicals. The main Objective: of this expert system is to provide an accurate diagnosis of lung cancer and the appropriate treatment options. In this paper, Methods: we present the design and implementation of (...) an expert system that can assist physicians in diagnosing lung cancer and determining the best course of treatment. The system provides an overview of the disease, its causes, symptoms, diagnosis, and treatment, along with relevant medical information. Results: The system was developed using the Clips expert system language and evaluated by medical professionals who found it to be an effective tool for diagnosing and treating lung cancer. Conclusion: The proposed expert system has the potential to improve patient outcomes and reduce healthcare costs associated with the treatment of lung cancer. (shrink)

Since its initial publication in 2018, Professor Anya Plutynski’s Explaining Cancer: Finding Order in Disorder has garnered a great deal of accolades.1 In 2021, The London School of Economics and Political Science conferred Professor Plutynski the Lakatos Award, recognizing the book’s significant contribution to the philosophy of science. On the heels of its recent reissuing as a paperback, it is an ideal time to revisit this remarkable work.

Abstract: This research explores the application of artificial neural networks (ANNs) in predicting cancer using a synthetically generated dataset designed for research purposes. The dataset comprises 10,000 pseudo-patient records, each characterized by gender, age, smoking history, fatigue, and allergy status, along with a binary indicator for the presence or absence of cancer. The 'Gender,' 'Smoking,' 'Fatigue,' and 'Allergy' attributes are binary, while 'Age' spans a range from 18 to 100 years. The study employs a three-layer ANN architecture to (...) develop a predictive model. The achieved accuracy of 97.24% and a low loss value of 0.02 indicate promising performance. Further analysis involves a comprehensive examination of the confusion matrix, precision, recall, and F1 score metrics, along with the ROC curve and AUC score, to provide a detailed understanding of the model's strengths and weaknesses. Additionally, considerations for cross-validation, hyperparameter tuning, and interpretability are discussed. It is emphasized that while the synthetic nature of the dataset allows for controlled experimentation, results should be cautiously interpreted and validated on authentic clinical data before extrapolation to real-world medical scenarios. This research serves as a valuable contribution to the exploration of predictive models for cancer detection, encouraging continued investigation and development in the field. (shrink)

In this thesis, I give a metascientific account of causality in medicine. I begin with two historical cases of causal discovery. These are the discovery of the causation of Burkitt’s lymphoma by the Epstein-Barr virus, and of the various viral causes suggested for cervical cancer. These historical cases then support a philosophical discussion of causality in medicine. This begins with an introduction to the Russo- Williamson thesis (RWT), and discussion of a range of counter-arguments against it. Despite these, I (...) argue that the RWT is historically workable, given a small number of modifications. I then expand Russo and Williamson’s account. I first develop their suggestion that causal relationships in medicine require some kind of evidence of mechanism. I begin with a number of accounts of mechanisms and produce a range of consensus features of them. I then develop this consensus position by reference to the two historical case studies with an eye to their operational competence. In particular, I suggest that it is mechanistic models and their representations which we are concerned with in medicine, rather than the mechanism as it exists in the world. -/- I then employ these mechanistic models to give an account of the sorts of evidence used in formulating and evaluating causal claims. Again, I use the two human viral oncogenesis cases to give this account. I characterise and distinguish evidence of mechanism from evidence of difference-making, and relate this to mechanistic models. I then suggest the relationship between types of evidence presents us with a means of tackling the reference-class problem. This sets the scene for the final chapter. Here, I suggest the manner in which these two different classes of evidence become integrated is also reflected in the way that developing research programmes change as their associated causal claims develop. (shrink)

Among all aspects, the unmet needs of healthcare information from the healthcare and illness-related domains have the potency to predict the unmet needs of emotional support from the emotional and relational domains in this population. The current study aims to examine the predictors of the needs for emotional support among FCGs of cancer patients by analyzing the demanded healthcare information, i.e., cancer-specific information, caregiver-specific information, therapy-specific information, information on cancer physical needs, information on alternative therapies, and information (...) on support services. (shrink)

Fact/value holism has become commonplace in philosophy of science, especially in feminist literature. However, that facts are bearers of empirical content, while values are not, remains a firmly-held distinction. I support a more thorough-going holism: both facts and values can function as empirical claims, related in a seamless, semantic web. I address a counterexample from Kourany where facts and values seem importantly discontinuous, namely, the simultaneous support by the Nazis of scientifically sound cancer research and morally unsound political policies. (...) I conclude that even by the criteria available at the time, Nazi cancer research was empirically weak, and the weaknesses in their research are continuous with their moral failures in just the ways predicted by the holism I support. (shrink)

It has been known for long time that the cosmic sound wave was there since the early epoch of the Universe. Signatures of its existence are abound. However, such an acoustic model of cosmology is rarely developed fully into a complete framework from the notion of space, cancer therapy up to the sky. This paper may be the first attempt towards such a complete description of the Universe based on classical wave equation of sound. It is argued that one (...) can arrive at a consistent description of space, elementary particles, Sachs-Wolfe acoustic theorem, up to a novel approach for cancer therapy, starting from this simple classical wave equation of sound. We also discuss a plausible extension of Acoustic Sachs-Wolfe theorem based on its analogue with Klein-Gordon equation to become Acoustic Sachs-Wolfe-Christianto-Smarandache-Umniyati (ASWoCSU) equation. It is our hope that the new proposed equation can be verified with observation data. But we admit that our model is still in its infancy, more researches are needed to fill all the missing details. (shrink)

The current study aims to examine how types of demanded healthcare information affect the FCG’s role in catalyzing the adaptation of female cancer patients (i.e., cancer-specific information, caregiver-specific information, therapy-specific information, information on cancer physical needs, information on alternative therapies, and information on support services).

Abstract: Lung cancer is the top reason of cancer-associated deaths globally. Surgery is the typical treatment for early-stage non-small cell lung cancer (NSCLC). Advancement in the knowledge of the biology of non-small cell lung cancer has shown molecular evidence used for systemic cancer therapy aiming metastatic disease, with a significant impact on patients’ overall survival (OS) and eminence of life. Though, a biopsy of overt metastases is an invasive technique restricted to assured positions and not (...) effortlessly satisfactory in the clinic. The examination of peripheral blood samples of cancer patients embodies a new basis of cancer-derived material, recognized as liquid biopsy, and its constituents (circulating tumour cells (CTCS), circulating free DNA (cfDNA), exosomes, and tumour-educated platelets (TEP)) may be gotten from nearly any body liquids. These constituents have shown to imitate features of the status of both the primary and metastatic diseases, aiding the clinicians to go towards a tailored medicine. In this paper, the reasons of lung cancer will be recognized and the risk elements that initiated the increase of infection, for instance Smoking, Disclosure to secondhand smoke, Disclosure to radon gas, Disclosure to asbestos and other compounds, Family past history of lung cancer, and decrease of the spread of disease and approaches of handling and prevention of lung cancer. (shrink)

In this paper we present applications of the ACGT Master Ontology (MO) which is a new terminology resource for a transnational network providing data exchange in oncology, emphasizing the integration of both clinical and molecular data. The development of a new ontology was necessary due to problems with existing biomedical ontologies in oncology. The ACGT MO is a test case for the application of best practices in ontology development. This paper provides an overview of the application of the ontology within (...) the ACGT project thus far. (shrink)

The purpose of this paper is to present a critique of the current view that reduces cancer to a cellular problem caused by specific gene mutations and to propose, instead, that such a problem might become more intelligible, if it is understood as a phenomenon that results from the breakdown of the morphological plan or Gestalt of the organism. Such and organism, in Aristotelian terms, is characterized for presenting a specific morphe or logos (form) and for having a telos (...) (end) to fulfill. A malignant tumor represents an entity separated from both the organic logos and the organic telos. According to the basic postulates of Semiophysics – a blend of Aristotelian physics and Catastrophe Theory developed by René Thom – an organism is a source (original) form individuated by a dominant pregnance that corresponds to its morphogenetic field. Here it is suggested that cancer in aged individuals might result from the progressive exhaustion of developmental constraints that regulate the process of ontogeny, that it is expected to go from the fertilized non-differentiated zygote to the mature fully developed organism, because there is no further point ahead in the developmental pathway past the reproductive age. Cancer in young individuals (before their reproductive maturity) may then be consequence of the premature derangement of such fundamental developmental constraints. In all cases the result is the loss of morphological coherence within the organism. Thus representing a conflict between an organized morphology (the organism) and a part of such a morphology that drifts towards an amorphous state (the tumor). (shrink)

Objective: Lung cancer is the most common cause of morbidity and mortality. Platinum-based chemotherapy, which is the primary line of treatment, offers limited benefit due to drug resistance and side effects. Berberine (BBR), which is characterised by its potent and safe anticancer activity, represents a promising combination option in chemotherapy. To overcome the limitations in lung cancer chemotherapy, we investigated whether BBR and cisplatin (CIS) exert synergistic effects on non-small cell lung cancer cell line (A549) based on (...) cytotoxicity and apoptotic response markers. -/- Methods: The potential cytotoxic effects of the combination treatment were evaluated using the MTT and Chou-Talalay methods. Elisa assays were also performed to measure the levels of the pro-apoptotic protein Bax and the effector protein caspase (Cas)-3. -/- Results: The results showed that BBR alone reduced A549 cell viability in a dose-dependent manner and synergized with CIS (CI =0.34±0.05 at IC50 concentrations). Elisa results showed that the combined treatment (both at IC50 concentrations) modulated apoptotic signalling pathways in A549 cells. Bax and Cas3 protein levels were dramatically enhanced in A549 cells treated with CIS +BBR compared to control (0.5% DMSO) (p < 0.001). -/- Conclusion: Our results suggest that BBR can synergistically enhance the therapeutic effect of CIS in A549 cells. The potential therapeutic efficacy of BBR as part of a combination in current chemotherapy should be supported by in-depth research and clinical studies on the molecular mechanisms associated with cancer. (shrink)