Ontology is one strategy for promoting interoperability of heterogeneous data through consistent tagging. An ontology is a controlled structured vocabulary consisting of general terms (such as “cell” or “image” or “tissue” or “microscope”) that form the basis for such tagging. These terms are designed to represent the types of entities in the domain of reality that the ontology has been devised to capture; the terms are provided with logical defi nitions thereby also supporting reasoning over the tagged data. Aim: This (...) paper provides a survey of the biomedical imaging ontologies that have been developed thus far. It outlines the challenges, particularly faced by ontologies in the fields of histopathological imaging and image analysis, and suggests a strategy for addressing these challenges in the example domain of quantitative histopathology imaging. The ultimate goal is to support the multiscale understanding of disease that comes from using interoperable ontologies to integrate imaging data with clinical and genomics data. (shrink)

Publication ethics is an important aspect of both the research and publication enterprises. It is particularly important in the field of biomedical science because published data may directly affect human health. In this article, we examine publication ethics policies in biomedical journals published in Central and Eastern Europe. We were interested in possible differences between East European countries that are members of the European Union (Eastern EU) and South-East European countries (South-East Europe) that are not members of the (...) European Union.The most common ethical issues addressed by all journals in the region were redundant publication, peer review process, and copyright or licensing details. Image manipulation, editors’ conflicts of interest and registration of clinical trialswere the least common ethical policies. Three aspects were significantly morecommon in journals published outside the EU: statements on the endorsement of international editorial standards, contributorship policy, and image manipulation.On the other hand, copyright or licensing information were more prevalent in journals published in the Eastern EU. The existence of significant differences amongbiomedical journals’ ethical policies calls for further research and active measuresto harmonize policies across journals. On the other hand, copyright or licensing information were more prevalent in journals published in the Eastern EU. The existence of significant differences among biomedical journals’ ethical policies calls for further research and active measures to harmonize policies across journals. (shrink)

Integrating medical imaging with computing technologies, such as Artificial Intelligence (AI) and its subsets: Machine learning (ML) and Deep Learning (DL) has advanced into an essential facet of present-day medicine, signaling a pivotal role in diagnostic decision-making and treatment plans (Huang et al., 2023). The significance of medical imaging is escalated by its sustained growth within the realm of modern healthcare (Varoquaux and Cheplygina, 2022). Nevertheless, the ever-increasing volume of medical images compared to the availability of imaging (...) experts. Biomedical experts and radiologists have resulted in a widening disparity, causing an excess and overwhelming workload on these healthcare professionals (Chen et al., 2021). Several studies indicate that the present-day biomedical radiologist is now saddled with the daunting task of interpreting an image almost every 10 seconds to keep pace with the burgeoning clinical demands (McDonald et al., 2015; Hosny et al., 2018; Lantsman et al., 2022). This cognitive drain has invariably led to inevitable consequences such as delays in diagnosis and an amplified risk of diagnostic errors – thus, the biomedical imaging aspect is in dire need of methods that would aid accurate diagnostics and analytics for improved decision making. In this review, the importance of AI-related technologies such as ML and/or DL methods are reviewed in relation to the processing of medical or biomedical images along with their potentials, challenges, and possible suggestions for future studies in the health landscape. The focus will be on machine learning methods associated with the medical field of image classification. (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)

According to the biomedical model of medicine, the subject of the illness event is the pathology rather than the person diagnosed with the disease. In this view, a body-self becomes a ‘patient’ body-object that can be enrolled in a therapeutic protocol, investigated, assessed, and transformed. How can it be possible for cancer patients to make sense of the opposite dimensions of their body-self and their body-diseased-object? Could a creative embodied approach enable the coping with trauma tied to the experience (...) of illness? By applying a phenomenological approach and auto-ethnographic analysis to the experience of cancer, this visual exploration provides support for rethinking the cancer event through a performative perspective. This work previews images and video material collected over ten years of haematological treatments, video dance performances and physical explorations. This work displays how processes of healing can be set in motion by creative embodied practices, physical explorations and unexpected journeys. By resisting the biomedical model and allowing the emergence of new meanings, it illustrates how dance and performative practices offer ground for transformation. (shrink)

Automatic detection of diseases and anatomical landmarks in medical images by the use of computers is important and considered a challenging process that could help medical diagnosis and reduce the cost and time of investigational procedures and refine health care systems all over the world. Recently, gastrointestinal (GI) tract disease diagnosis through endoscopic image classification is an active research area in the biomedical field. Several GI tract disease classification methods based on image processing and machine learning techniques have been (...) proposed by diverse research groups in the recent past. However, yet effective and comprehensive deep ensemble neural network-based classification model with high accuracy classification results is not available in the literature. In this thesis, we review ways and mechanisms to use deep learning techniques to research on multi-disease computer-aided detection about gastrointestinal and identify these images. We re-trained five state-of-the-art neural network architectures, VGG16, ResNet, MobileNet, Inception-v3, and Xception on the Kvasir dataset to classify eight categories that include an anatomical landmark (pylorus, z-line, cecum), a diseased state (esophagitis, ulcerative colitis, polyps), or a medical procedure (dyed lifted polyps, dyed resection margins) in the Gastrointestinal Tract. Our models have showed results with a promising accuracy which is a remarkable performance with respect to the state-of-the-art approaches. The resulting accuracies achieved using VGG, ResNet, MobileNet, Inception-v3, and Xception were 98.3%, 92.3%, 97.6%, 90% and 98.2%, respectively. As it appears, the most accurate result has been achieved when retraining VGG16 and Xception neural networks with accuracy reache to 98% due to its high performance on training on ImageNet dataset and internal structure that support classification problems. (shrink)

This is the first volume of the Encyclopedia of Neutrosophic Researchers, edited from materials offered by the authors who responded to the editor’s invitation. The 78 authors are listed alphabetically. The introduction contains a short history of neutrosophics, together with links to the main papers and books. -/- Neutrosophic set, neutrosophic logic, neutrosophic probability, neutrosophic statistics, neutrosophic measure, neutrosophic precalculus, neutrosophic calculus and so on are gaining significant attention in solving many real life problems that involve uncertainty, impreciseness, vagueness, incompleteness, (...) inconsistent, and indeterminacy. -/- In the past years the fields of neutrosophics have been extended and applied in various fields, such as: artificial intelligence, data mining, soft computing, decision making in incomplete / indeterminate / inconsistent information systems, image processing, computational modelling, robotics, medical diagnosis, biomedical engineering, investment problems, economic forecasting, social science, humanistic and practical achievements. (shrink)

Disorders of consciousness include coma, the vegetative state and the minimally conscious state. Such patients are often regarded as unconscious. This has consequences for end of life decisions for these patients: it is much easier to justify withdrawing life support for unconscious than conscious patients. Recent brain imaging research has however suggested that some patients may in fact be conscious.

This is the fourth volume of the Encyclopedia of Neutrosophic Researchers, edited from materials offered by the authors who responded to the editor’s invitation. The authors are listed alphabetically. The introduction contains a short history of neutrosophics, together with links to the main papers and books. Neutrosophic set, neutrosophic logic, neutrosophic probability, neutrosophic statistics, neutrosophic measure, neutrosophic precalculus, neutrosophic calculus and so on are gaining significant attention in solving many real life problems that involve uncertainty, impreciseness, vagueness, incompleteness, inconsistent, and (...) indeterminacy. In the past years the fields of neutrosophics have been extended and applied in various fields, such as: artificial intelligence, data mining, soft computing, decision making in incomplete / indeterminate / inconsistent information systems, image processing, computational modelling, robotics, medical diagnosis, biomedical engineering, investment problems, economic forecasting, social science, humanistic and practical achievements. (shrink)

This paper critically assesses the model of evaluation of scientific research for democratic societies defended by Philip Kitcher. The “significant truth” approach proposes a viable alternative to two classic images of science: that of the “critics”, who believe that science always serves the interests of the powerful and that of the “faithful”, who argue that the pursuit of scientific knowledge is always valuable and necessary. However, the democratic justification of Kitcher’s proposal is not compatible with the ethical problems generated by (...) the international biomedical research in developing countries. To overcome this problem, I revise the national democratic framing of the significant truth approach in light of the theory of justice of John Rawls. (shrink)

This is the first volume of the Encyclopedia of Neutrosophic Researchers, edited from materials offered by the authors who responded to the editor’s invitation. The authors are listed alphabetically. The introduction contains a short history of neutrosophics, together with links to the main papers and books. Neutrosophic set, neutrosophic logic, neutrosophic probability, neutrosophic statistics, neutrosophic measure, neutrosophic precalculus, neutrosophic calculus and so on are gaining significant attention in solving many real life problems that involve uncertainty, impreciseness, vagueness, incompleteness, inconsistent, and (...) indeterminacy. In the past years the fields of neutrosophics have been extended and applied in various fields, such as: artificial intelligence, data mining, soft computing, decision making in incomplete / indeterminate / inconsistent information systems, image processing, computational modelling, robotics, medical diagnosis, biomedical engineering, investment problems, economic forecasting, social science, humanistic and practical achievements. (shrink)

This is the third volume of the Encyclopedia of Neutrosophic Researchers, edited from materials offered by the authors who responded to the editor’s invitation. The authors are listed alphabetically. The introduction contains a short history of neutrosophics, together with links to the main papers and books. Neutrosophic set, neutrosophic logic, neutrosophic probability, neutrosophic statistics, neutrosophic measure, neutrosophic precalculus, neutrosophic calculus and so on are gaining significant attention in solving many real life problems that involve uncertainty, impreciseness, vagueness, incompleteness, inconsistent, and (...) indeterminacy. In the past years the fields of neutrosophics have been extended and applied in various fields, such as: artificial intelligence, data mining, soft computing, decision making in incomplete / indeterminate / inconsistent information systems, image processing, computational modelling, robotics, medical diagnosis, biomedical engineering, investment problems, economic forecasting, social science, humanistic and practical achievements. (shrink)

When many people think of bioethics, they think of gripping issues in clinical medicine such as end-of-life decision-making, controversies in biomedical research such as that over work with stem cells, or issues in allocating scarce health-care resources such as organs or money. The term “bioethics” may evoke images of moral controversies being discussed on news programs and talk shows. But this “controversy of the day” focus often treats ethical issues in medicine superficially, for it addresses them as if they (...) could be examined and discussed in isolation from the context in which they are situated. Such a focus on the latest controversies fails to take into account that medicine is a social institution and that the controversies in bioethics often reflect deeper social and moral issues that transcend the boundaries of medicine and ethics. If one moves beyond the issue-of-the-day approach to bioethics, one can see that the field must address these deeper issues. (shrink)

Cardiotocography data uncertainty is a critical task for the classification in biomedical field. Constructing good and efficient classifier via machine learning algorithms is necessary to help doctors in diagnosing the state of fetus heart rate. *e proposed neutrosophic diagnostic system is an Interval Neutrosophic Rough Neural Network framework based on the backpropagation algorithm. It benefits from the advantages of neutrosophic set theory not only to improve the performance of rough neural networks but also to achieve a better performance than (...) the other algorithms. *e experimental results visualize the data using the boxplot for better understanding of attribute distribution. *e performance measurement of the confusion matrix for the proposed framework is 95.1, 94.95, 95.2, and 95.1 concerning accuracy rate, precision, recall, and F1-score, respectively. WEKA application is used to analyse cardiotocography data performance measurement of different algorithms, e.g., neural network, decision table, the nearest neighbor, and rough neural network. *e comparison with other algorithms shows that the proposed framework is both feasible and efficient classifier. Additionally, the receiver operation characteristic curve displays the proposed framework classifications of the pathologic, normal, and suspicious states by 0.93, 0.90, and 0.85 areas that are considered high and acceptable under the curve, respectively. Improving the performance measurements of the proposed framework by removing ineffective attributes via feature selection would be suitable advancement in the future. Moreover, the proposed framework can also be used in various real-life problems such as classification of coronavirus, social media, and satellite image. (shrink)

The genomics “revolution” is spreading. Originating in the molecular life sciences, it initially affected a number of biomedical research fields such as cancer genomics and clinical genetics. Now, however, a new “wave” of genomic bioinformation is transforming a widening array of disciplines, including those that address the social, historical and cultural dimensions of human life. Increasingly, bioinformation is affecting “human sciences” such as psychiatry, psychology, brain research, behavioural research (“behavioural genomics”), but also anthropology and archaeology (“bioarchaeology”). Thus, bioinformatics is (...) having an impact on how we define and understand ourselves, how identities are formed and constituted, and, finally, on how we (on the basis of these redefined identities) assess and address some of the more concrete societal issues involved in genomics governance in various settings. This article explores how genomics and bioinformation, by influencing research agendas in the human sciences and the humanities, are affecting our self-image, our identity, the way we see ourselves. The impact of bioinformation on self-understanding will be assessed on three levels: (1) the collective level (the impact of comparative genomics on our understanding of human beings as a species), (2) the individual level (the impact of behavioural genomics on our understanding of ourselves as individuals), and (3) the genealogical level (the impact of population genomics on our understanding of human history, notably early human history). This threefold impact will be assessed from two seemingly incompatible philosophical perspectives, namely a “humanistic” perspective (represented in this article by Francis Fukuyama) and a “post-humanistic” one (represented by Peter Sloterdijk). On the basis of this analysis it will be concluded that, rather than focussing on human “enhancement” by adding or deleting genes, genome-oriented practices of the Self will focus on using genomics information in the context of identity-formation. Genomic bioinformation will increasingly be built into our self-images and used in order to tailor and adapt our practices of Self to our “personalised” genome. We will keep working on ourselves, no doubt, not by modifying our genomes, but rather by fine-tuning our behaviour. What we are experiencing is a bioinformatisation of the life-world. Genomics-based technologies will increasingly pervade our daily lives, our autobiographies and narratives, as well as our anthropologies, rather than our genomes as such. (shrink)

Despite the recent advances in information and communication technology that have increased our ability to store and circulate information, the task of ensuring that the right sorts of information gets to the right sorts of people remains. We argue that the many efforts underway to develop efficient means for sharing information across healthcare systems and organizations would benefit from a careful analysis of human action in healthcare organizations. This in turn requires that the management of information and knowledge within healthcare (...) organizations be combined with models of resources and processes of patient care that are based on a general ontology of social interaction. The Health Level 7 (HL7) is one of several ANSI-accredited Standards Developing Organizations operating in the healthcare arena. HL7 has advanced a widely used messaging standard that enables healthcare applications to exchange clinical and administrative data in digital form. HL7 focuses on the interface requirements of the entire healthcare system and not exclusively on the requirements of one area of healthcare such as pharmacy, medical devices, imaging or insurance transactions. This has inspired the development of a powerful abstract model of patient care called the Reference Information Model (RIM). The present paper begins with an overview of the core classes of the HL7 (Version 3) RIM and a brief discussion of its “actcentered” view of healthcare. Central to this account is what is called the life cycle of events. A clinical action may progress from defined, through planned and ordered, to executed. These modalities of an action are represented as the mood of the act. We then outline the basis of an ontology of organizations, starting from the theory of speech Acts, and apply this ontology to the HL7 RIM. Special attention is given to the sorts of preconditions that must be satisfied for the successful performance of a speech act and to the sorts of entities to which speech acts give rise (e.g. obligations, claims, commitments, etc.). Finally we draw conclusions for the efficient communication and management of medical information and knowledge within and between healthcare organizations, paying special attention to the role that medical documents play in such organizations. (shrink)

Biomedical ontologies exist to serve integration of clinical and experimental data, and it is critical to their success that they be put to widespread use in the annotation of data. How, then, can ontologies achieve the sort of user-friendliness, reliability, cost-effectiveness, and breadth of coverage that is necessary to ensure extensive usage? Methods: Our focus here is on two different sets of answers to these questions that have been proposed, on the one hand in medicine, by the SNOMED CT (...) community, and on the other hand in biology, by the OBO Foundry. We address more specifically the issue as to how adherence to certain development principles can advance the usability and effectiveness of an ontology or terminology resource, for example by allowing more accurate maintenance, more reliable application, and more efficient interoperation with other ontologies and information resources. Results: SNOMED CT and the OBO Foundry differ considerably in their general approach.Nevertheless, a general trend towards more formal rigor and cross-domain interoperability can be seen in both and we argue that this trend should be accepted by all similar initiatives in the future. Conclusions: Future efforts in ontology development have to address the need for harmonization and integration of ontologies across disciplinary borders, and for this, coherent formalization of ontologies is a prerequisite. (shrink)

In the management of biomedical data, vocabularies such as ontologies and terminologies (O/Ts) are used for (i) domain knowledge representation and (ii) interoperability. The knowledge representation role supports the automated reasoning on, and analysis of, data annotated with O/Ts. At an interoperability level, the use of a communal vocabulary standard for a particular domain is essential for large data repositories and information management systems to communicate consistently with one other. Consequently, the interoperability benefit of selecting a particular O/T as (...) a standard for data exchange purposes is often seen by the end-user as a function of the number of applications using that vocabulary (and, by extension, the size of the user base). Furthermore, the adoption of an O/T as an interoperability standard requires confidence in its stability and guaranteed continuity as a resource. (shrink)

In biomedical ethics, there is widespread acceptance of moral realism, the view that moral claims express a proposition and that at least some of these propositions are true. Biomedical ethics is also in the business of attributing moral obligations, such as “S should do X.” The problem, as we argue, is that against the background of moral realism, most of these attributions are erroneous or inaccurate. The typical obligation attribution issued by a biomedical ethicist fails to truly (...) capture the person's actual obligations. We offer a novel argument for rife error in obligation attribution. The argument starts with the idea of an epistemic burden. Epistemic burdens are all of those epistemic obstacles one must surmount in order to achieve some aim. Epistemic burdens shape decision-making such that given two otherwise equal options, a person will choose the option that has the lesser of epistemic burdens. Epistemic burdens determine one's potential obligations and, conversely, their non-obligations. The problem for biomedical ethics is that ethicists have little to no access to others' epistemic burdens. Given this lack of access and the fact that epistemic burdens determine potential obligations, biomedical ethicists often can only attribute accurate obligations out of luck. This suggests that the practice of attributing obligations in biomedical ethics is rife with error. To resolve this widespread error, we argue that this practice should be abolished from the discourse of biomedical ethics. (shrink)

We begin at the beginning, with an outline of Aristotle’s views on ontology and with a discussion of the influence of these views on Linnaeus. We move from there to consider the data standardization initiatives launched in the 19th century, and then turn to investigate how the idea of computational ontologies developed in the AI and knowledge representation communities in the closing decades of the 20th century. We show how aspects of this idea, particularly those relating to the use of (...) the term 'concept' in ontology development, influenced SNOMED CT and other medical terminologies. Against this background we then show how the Foundational Model of Anatomy, the Gene Ontology, Basic Formal Ontology and other OBO Foundry ontologies came into existence and discuss their role in the development of contemporary biomedical informatics. (shrink)

The Ontology for Biomedical Investigations (OBI) is an ontology that provides terms with precisely defined meanings to describe all aspects of how investigations in the biological and medical domains are conducted. OBI re-uses ontologies that provide a representation of biomedical knowledge from the Open Biological and Biomedical Ontologies (OBO) project and adds the ability to describe how this knowledge was derived. We here describe the state of OBI and several applications that are using it, such as adding (...) semantic expressivity to existing databases, building data entry forms, and enabling interoperability between knowledge resources. OBI covers all phases of the investigation process, such as planning, execution and reporting. It represents information and material entities that participate in these processes, as well as roles and functions. Prior to OBI, it was not possible to use a single internally consistent resource that could be applied to multiple types of experiments for these applications. OBI has made this possible by creating terms for entities involved in biological and medical investigations and by importing parts of other biomedical ontologies such as GO, Chemical Entities of Biological Interest (ChEBI) and Phenotype Attribute and Trait Ontology (PATO) without altering their meaning. OBI is being used in a wide range of projects covering genomics, multi-omics, immunology, and catalogs of services. OBI has also spawned other ontologies (Information Artifact Ontology) and methods for importing parts of ontologies (Minimum information to reference an external ontology term (MIREOT)). The OBI project is an open cross-disciplinary collaborative effort, encompassing multiple research communities from around the globe. To date, OBI has created 2366 classes and 40 relations along with textual and formal definitions. The OBI Consortium maintains a web resource providing details on the people, policies, and issues being addressed in association with OBI. (shrink)

Biomedical technologies can increasingly be used not only to combat disease, but also to augment the capacities or traits of normal, healthy people – a practice commonly referred to as biomedical enhancement. Perhaps the best‐established examples of biomedical enhancement are cosmetic surgery and doping in sports. But most recent scientific attention and ethical debate focuses on extending lifespan, lifting mood, and augmenting cognitive capacities.

The concept of ‘the image’ can be given historical, conceptual, aesthetic and moral specifications. This essay sets out some of the scholarly issues in the dense semantic field of ‘the image’. In particular, the essay considers how the meaning of the image is often determined in relation to the opposition between sensible form and intelligible idea. Specific attention is given to Kantian aesthetics, which inaugurates a specific way of understanding the sensible form as a mode of processing moral ideas.

Given certain standard assumptions-that particular sentences are meaningful, for example, and do genuinely self-attribute their own falsity-the paradoxes appear to show intriguing patterns of generally unstable semantic behavior. In what follows we want to concentrate on those patterns themselves: the pattern of the Liar, for example, which if assumed either true or false appears to oscillate endlessly between truth and falsehood.

Some have suggested that images can be arguments. Images can certainly bolster the acceptability of individual premises. We worry, though, that the static nature of images prevents them from ever playing a genuinely argumentative role. To show this, we call attention to a dilemma. The conclusion of a visual argument will either be explicit or implicit. If a visual argument includes its conclusion, then that conclusion must be demarcated from the premise or otherwise the argument will beg the question. If (...) a visual argument does not include its conclusion, then the premises on display must license that specific conclusion and not its opposite, in accordance with some demonstrable rationale. We show how major examples from the literature fail to escape this dilemma. Drawing inspiration from the graphical logic of C. S. Peirce, we suggest instead that images can be manipulated in a way that overcomes the dilemma. Diagrammatic reasoning can take one stepwise from an initial visual layout to a conclusion—thereby providing a principled rationale that bars opposite conclusions—and the visual inscription of this correct conclusion can come afterward in time—thereby distinguishing the conclusion from the premises. Even though this practical application of Peirce’s logical ideas to informal contexts requires that one make adjustments, we believe it points to a dynamic conception of visual argumentation that will prove more fertile in the long run. (shrink)

The senses present their content in the form of images, three-dimensional arrays of located sense features. Peacocke’s “scenario content” is one attempt to capture image content; here, a richer notion is presented, sensory images include located objects and features predicated of them. It is argued that our grasp of the meaning of these images implies that they have propositional content. Two problems concerning image content are explored. The first is that even on an enriched conception, image content has certain expressive (...) limitations. In particular, it cannot express absolute location and time (as opposed to spatiotemporal relations) or logical complexity. Yet, perceptual experience does seem to express certain absolute locations—namely, here and now. How can it do so? Secondly, image content cannot exhaust the significance of perceptual states. This is proved by noting that perception, memory, and anticipation can have the same image content. Yet they have different significance. These problems show that some of the significance of sensory states comes from outside the image. (shrink)

Most research on image schema examined the meaning configuration of words connotation. However, previous studies of adjectives are meaningful in cognitive linguistics because they provide insight into how those adjectives are involved with psychological movement. In this sense, from the perspective of cognitive linguistics, one’s conceptualization and cognition are closely associated with their bodily experience and surroundings; adjectives are no exception. The varieties of transformations of image schemas lay the foundation for the conception and perception. Accordingly, this study is an (...) investigation into the perception of adjectives and psychological activities associated with image schema. Data in this study come from adjectives in the novel The Great Gatsby, which were tagged and calculated with the help of software Python and the NLTK package. The results demonstrate that a significant amount of adjectives were used in the novel. Moreover, Nick’s psychological activities changed significantly from the SOURCE to the DESTINATION schematic stage, which is uncovered by his expression of adjectives. Finally, the results further suggest that transformations of image schema as BALANCE, CONTAINER, and PATH work together to motivate one’s linguistic expression of adjectives. The present findings have several implications for research on lexicons and literacy interpretation from cognitive linguistics. (shrink)

1. Biomedical sciences are fast-growing fields with unprecedented speed of research outputs, especially in the quantities of papers. Philosophers aiming to study ongoing biomedical changes face cha...

The National Center for Biomedical Ontology is now in its seventh year. The goals of this National Center for Biomedical Computing are to: create and maintain a repository of biomedical ontologies and terminologies; build tools and web services to enable the use of ontologies and terminologies in clinical and translational research; educate their trainees and the scientific community broadly about biomedical ontology and ontology-based technology and best practices; and collaborate with a variety of groups who develop (...) and use ontologies and terminologies in biomedicine. The centerpiece of the National Center for Biomedical Ontology is a web-based resource known as BioPortal. BioPortal makes available for research in computationally useful forms more than 270 of the world's biomedical ontologies and terminologies, and supports a wide range of web services that enable investigators to use the ontologies to annotate and retrieve data, to generate value sets and special-purpose lexicons, and to perform advanced analytics on a wide range of biomedical data. (shrink)

This essay explores Jonas’s multifaceted and rich enquiries into the notion of image. In particular, it argues that reflecting on the “image” helps Jonas clarify the unique condition of human existence, where the twine of thought and being reveals a paradoxical (and yet crucial) relationship between time and eternity, change and permanence, immanence and transcendence. The employ of the interpretative device provided by the image enables a nuanced understanding of the human complexity which goes beyond the partial and reductive descriptions (...) of relativistic immanentism, on the one hand, and immutable transcendence, on the other. By commenting upon its anthropological, aesthetic, and ethical significance, we propose that the study of Jonas’s thoughts on the image not only offers valuable insights into the philosophical understanding of such a fascinating object, but also sheds a new and interesting light on the unity of his oeuvre. (shrink)

In this article, we analyse how researchers use the categories of race and ethnicity with reference to genetics and genomics. We show that there is still considerable conceptual “messiness” (despite the wide-ranging and popular debate on the subject) when it comes to the use of ethnoracial categories in genetics and genomics that among other things makes it difficult to properly compare and interpret research using ethnoracial categories, as well as draw conclusions from them. Finally, we briefly reconstruct some of the (...) biases of reductionism to which geneticists (as well as other researchers referring to genetic methods and explanations) are particularly exposed to, and we analyse the problem in the context of the biologization of ethnoracial categories. Our work constitutes a novel, in-depth contribution to the debate about reporting race and ethnicity in biomedical and health research. First, we reconstruct the theoretical background assumptions about racial ontology which researchers implicitly presume in their studies with the aid of a sample of recent papers published in medical journals about COVID-19. Secondly, we use the typology of the biases of reductionism to the problem of biologization of ethnoracial categories with reference to genetics and genomics. (shrink)

The goal of the OBO (Open Biomedical Ontologies) Foundry initiative is to create and maintain an evolving collection of non-overlapping interoperable ontologies that will offer unambiguous representations of the types of entities in biological and biomedical reality. These ontologies are designed to serve non-redundant annotation of data and scientific text. To achieve these ends, the Foundry imposes strict requirements upon the ontologies eligible for inclusion. While these requirements are not met by most existing biomedical terminologies, the latter (...) may nonetheless support the Foundry’s goal of consistent and non-redundant annotation if appropriate mappings of data annotated with their aid can be achieved. To construct such mappings in reliable fashion, however, it is necessary to analyze terminological resources from an ontologically realistic perspective in such a way as to identify the exact import of the ‘concepts’ and associated terms which they contain. We propose a framework for such analysis that is designed to maximize the degree to which legacy terminologies and the data coded with their aid can be successfully used for information-driven clinical and translational research. (shrink)

Motivated by a recent trend that advocates a reassessment of the aim of medical science and clinical practice, this paper investigates the epistemic aims of biomedical research. Drawing on contemporary discussions in epistemology and the philosophy of science, along with a recent study on scurvy, this paper (1) explores the concept of understanding as the aim of scientific inquiry and (2) establishes a framework that will guide the examination of its forms in biomedical research. Using the case of (...) Tuberculosis (TB), (3) it is argued that grasping a mechanistic explanation is crucial for reaching a threshold of understanding at which we may speak of an objectual, biomedical understanding of TB. (shrink)

The paper is an introduction to the third issue of the Journal for the Philosophy of Language, Mind and the Arts. The authors give an account of the theories that have most enriched the study of images since the second half of the twentieth century: analytical philosophy and visual culture studies. A distinction is made between the two philosophical traditions. On the one hand, in particular within the context of analytic philosophy, images have been studied as single entities in relationship (...) with both a referent and the perceptual or interpretive abilities of an observer. On the other hand, thanks in particular to the iconographic tradition inaugurated by Aby Warburg, images have been analyzed in their multiplicity, in their mutual relationship, both synchronically and diachronically. (shrink)

An explicit formal-ontological representation of entities existing at multiple levels of granularity is an urgent requirement for biomedical information processing. We discuss some fundamental principles which can form a basis for such a representation. We also comment on some of the implicit treatments of granularity in currently available ontologies and terminologies (GO, FMA, SNOMED CT).

It is only by fixing on agreed meanings of terms in biomedical terminologies that we will be in a position to achieve that accumulation and integration of knowledge that is indispensable to progress at the frontiers of biomedicine. Standardly, the goal of fixing meanings is seen as being realized through the alignment of terms on what are called ‘concepts’. Part I addresses three versions of the concept-based approach – by Cimino, by Wüster, and by Campbell and associates – and (...) surveys some of the problems to which they give rise, all of which have to do with a failure to anchor the terms in terminologies to corresponding referents in reality. Part II outlines a new, realist solution to this anchorage problem, which sees terminology construction as being motivated by the goal of alignment not on concepts but on the universals (kinds, types) in reality and thereby also on the corresponding instances (individuals, tokens). We outline the realist approach, and show how on its basis we can provide a benchmark of correctness for terminologies which will at the same time allow a new type of integration of terminologies and electronic health records. We conclude by outlining ways in which the framework thus defined might be exploited for purposes of diagnostic decision-support. (shrink)

Without doubt, there is a great diversity of scientific images both with regard to their appearances and their functions. Diagrams, photographs, drawings, etc. serve as evidence in publications, as eye-catchers in presentations, as surrogates for the research object in scientific reasoning. This fact has been highlighted by Stephen M. Downes who takes this diversity as a reason to argue against a unifying representation-based account of how visualisations play their epistemic role in science. In the following paper, I will suggest an (...) alternative explanation of the diversity of scientific images. This account refers to processes which are caused by the social setting of science. What exactly is meant by this, I will spell out with the aid of Ludwik Fleck’s theory of the social mechanisms of scientific communication. (shrink)

While representation learning techniques have shown great promise in application to a number of different NLP tasks, they have had little impact on the problem of ontology matching. Unlike past work that has focused on feature engineering, we present a novel representation learning approach that is tailored to the ontology matching task. Our approach is based on embedding ontological terms in a high-dimensional Euclidean space. This embedding is derived on the basis of a novel phrase retrofitting strategy through which semantic (...) similarity information becomes inscribed onto fields of pre-trained word vectors. The resulting framework also incorporates a novel outlier detection mechanism based on a denoising autoencoder that is shown to improve performance. An ontology matching system derived using the proposed framework achieved an F-score of 94% on an alignment scenario involving the Adult Mouse Anatomical Dictionary and the Foundational Model of Anatomy ontology (FMA) as targets. This compares favorably with the best performing systems on the Ontology Alignment Evaluation Initiative anatomy challenge. We performed additional experiments on aligning FMA to NCI Thesaurus and to SNOMED CT based on a reference alignment extracted from the UMLS Metathesaurus. Our system obtained overall F-scores of 93.2% and 89.2% for these experiments, thus achieving state-of-the-art results. (shrink)

This article is part of a For-Discussion-Section of Methods of Information in Medicine about the paper "Biomedical Informatics: We Are What We Publish", written by Peter L. Elkin, Steven H. Brown, and Graham Wright. It is introduced by an editorial. This article contains the combined commentaries invited to independently comment on the Elkin et al. paper. In subsequent issues the discussion can continue through letters to the editor.

In this paper, I begin with an account of the initial distinction between likenesses and appearances, a distinction which may resemble the difference between sophists and philosophers. That distinction first arises immediately after the puzzling appearance of the noble sophist, who seems to occupy an odd space in between sophist and philosopher. In the second section, I look more closely at the noble sophist, and on what that figure might tell us about images and the use of images. I also (...) attempt to use the insights provided by the noble sophist in an investigation of the kind of images that Plato the author produces. This raises the question of the general notion of image as it appears in the Sophist, and especially of the dual nature of all images, which in turn invites reflection on certain features of the examination of being and non-being late in the dialogue. Finally, I return to the deception inherent in images, and I argue that this dialogue does not present the possibility of completely honest images. Nevertheless, I hope to show that some uses of deceptions and images are better than others. (shrink)

There is the tension between, on the one hand, Wittgenstein’s not giving theoretical weight to metaphor, and on the other, his exuberant use of it. On a more fundamental level, there is a straightforward contradiction between Wittgenstein’s claim of the primordial literalness of everyday language, and his stress on the multiplicity and flexibility of language-games. Wittgenstein’s problem was that he did not succeed in making his ideas on metaphor, and indeed his ideas on metaphor and images, converge with the main (...) drift of TS 227 (the so-called ‘Part I’ of the so-called ‘Philosophical Investigations’). It was this divergence, I believe, that prevented him from rounding out his later philosophy. (shrink)

In January 2024, non-consensual deepfakes came to public attention with the spread of AI generated sexually abusive images of Taylor Swift. Although this brought new found energy to the debate on what some call non-consensual synthetic intimate images (i.e. images that use technology such as AI or photoshop to make sexual images of a person without their consent), female celebrities like Swift have had deepfakes like these made of them for years. In 2017, a Reddit user named “deepfakes” posted several (...) videos in which he had used opensource machine learning tools to swap the faces of female celebrities on to the faces of female porn actors, displaying what appeared to be live video footage of the celebrity engaging in sex acts she never engaged in. Since that time, deepfake technology has advanced astronomically. What once were choppy sexualized videos are now nearly flawless videos that can be difficult to distinguish from a real video. According to recent research on deepfakes by Sensity AI, this technology has been used primarily on women to create sexual videos. These women’s sexual autonomy has been co-opted for the purposed of gratifying men’s sexual pleasure, but have also been used in campaigns to delegitimize and humiliate female journalists and politicians. In Canada, civil and criminal legislation has addressed the non-consensual distribution of intimate images, but in only a few provinces – British Columbia, New Brunswick, Prince Edward Island and Saskatchewan – does this offence include altered images that could include deepfakes. This paper explores the evolution of synthetic technology such as AI image generators and Canada’s legal responses to the non-consensual sharing of intimate images. (shrink)

Current debates surrounding the virtues and shortcomings of randomization are symptomatic of a lack of appreciation of the fact that causation can be inferred by two distinct inference methods, each requiring its own, specific experimental design. There is a non-statistical type of inference associated with controlled experiments in basic biomedical research; and a statistical variety associated with randomized controlled trials in clinical research. I argue that the main difference between the two hinges on the satisfaction of the comparability requirement, (...) which is in turn dictated by the nature of the objects of study, namely homogeneous or heterogeneous populations of biological systems. Among other things, this entails that the objection according to which randomized experiments fail to provide better evidence for causation because randomization cannot guarantee comparability is mistaken. (shrink)

In contemporary healthcare, medical image categorization is essential for illness prediction, diagnosis, and therapy planning. The emergence of digital imaging technology has led to a significant increase in research into the use of machine learning (ML) techniques for the categorization of images in medical data. We provide a thorough summary of recent developments in this area in this review, using knowledge from the most recent research and cutting-edge methods.We begin by discussing the unique challenges and opportunities associated with medical (...) image classification, including the complexity of anatomical structures, variability in imaging modalities, and the need for interpretability and reliability in clinical settings. Subsequently, we survey a wide range of ML algorithms and techniques employed for medical image classification, including traditional methods such as support vector machines and k-nearest neighbors, as well as deep learning approaches like convolutional neural networks (CNNs) and recurrent neural networks (RNNs). Furthermore, we examine key considerations in dataset preparation, feature extraction, and model evaluation specific to medical image classification tasks. We highlight the importance of large, annotated datasets, transfer learning, and data augmentation techniques in enhancing model performance and generalization. (shrink)

To enhance the treatment of relations in biomedical ontologies we advance a methodology for providing consistent and unambiguous formal definitions of the relational expressions used in such ontologies in a way designed to assist developers and users in avoiding errors in coding and annotation. The resulting Relation Ontology can promote interoperability of ontologies and support new types of automated reasoning about the spatial and temporal dimensions of biological and medical phenomena.

Advanced medical imaging, such as CT, fMRI and PET, has undergone enormous progress in recent years, both in accuracy and utilization. Such techniques often bring with them an illusion of immediacy, the idea that the body and its diseases can be directly inspected. In this paper we target this illusion and address the issue of the reliability of advanced imaging tests as knowledge procedures, taking positron emission tomography in oncology as paradigmatic case study. After individuating a suitable notion (...) of reliability, we argue that PET is a highly theory-laden and non-immediate knowledge procedure, in spite of the photographic-like quality of the images it delivers; the diagnostic conclusions based on the interpretation of PET images are population-dependent; PET images require interpretation, which is inherently observer-dependent and therefore variable. We conclude with a three-step methodological proposal for enhancing the reliability of advanced medical imaging. (shrink)

This chapter explores the role that non-textual narrations of biblical stories can play in Christian life and practice. Our case study is the Shrine of Divine Mercy in Kabuga, Rwanda. The stations at the shrine tell the story of Jesus’s life and passion, incorporating images from the Catholic devotional tradition of Divine Mercy and elements evoking the Rwandan genocide. While many philosophical accounts of narratives presuppose that narratives are textual, material and visual art like the Kabuga shrine can also be (...) narrative, in that, like text, material and visual art can selectively represent multiple events and connections between them. We argue that material-visual narratives like the shrine can be effective in achieving commonly identified functions of narratives, such as focusing attention, immersing in a story, engaging the emotions, and fostering a common perspective on the world. We further argue that material-visual art is well-suited to narrating the Gospel in particular, for it can present the Gospel story alongside other stories (in this case, the story of the Rwandan genocide) and in so doing reframe these other stories in light of the Gospel. (shrink)

Although better known for his phenomenology of perception and the perceived world, Merleau-Ponty’s writings also contain the outlines of a rich and unique account of the imagination and the imaginary. In this paper, I explicate the phenomenology of the image that Merleau-Ponty develops throughout his work. I show how Merleau-Ponty develops this account of the image in critical response to Sartre and in a way that follows from his own descriptions of what painters do when they paint and of what (...) we experience when we look at their paintings. The investigation of the particular mode of being of images leads to a consideration of the body and Merleau-Ponty’s later ontology. (shrink)

In order to maintain the existence of the business, it always creates and implements various marketingstrategies to maintain and maintain business operations in the midst of fierce business competition. Allbusinesses have competition so this makes the company must have a strategy to be able to excel incompetition. Companies must be able to know how to retain their customers so as not to turn to competitors.Especially in the field of coffee drinks business which is currently being rife in Surabaya. This research (...) usesa Quantitative Approach is a research approach that uses data in the form of figures from survey answersdistributed to research samples and analyzed using statistical analysis techniques. The partial regressionresults (t-test) showed the results of the brand image proved to have a significant effect on the decision topurchase coffee drinks at Janji Jiwa Royal Plaza Surabaya. Value is proven to have a significant effect oncoffee beverage purchase decisions at Janji Jiwa Royal Surabaya. Simultaneous regression analysis (F-test)proved to have a significant effect on brand image and value on coffee beverage purchase decisions at JanjiJiwa Royal Surabaya. (shrink)