Results for 'Classification'

447 found
Order:
  1. Mango Classification Using Deep Learning.Alaa Soliman Abu Mettleq, Ibtesam M. Dheir, Abeer A. Elsharif & Samy S. Abu-Naser - 2020 - International Journal of Academic Engineering Research (IJAER) 3 (12):22-29.
    Abstract: In worldwide, there are several hundred cultivars of mango. Depending on the cultivar, mango fruit varies in size, shape, sweetness, skin color, and flesh color which may be pale yellow, gold, or orange. Where there are more than 15 types of manga. In this paper, two types Mango classification approach is presented with a dataset that contains approximately 1200 images. Convolutional Neural Network (CNN) algorithms, a deep learning technique extensively applied to image recognition was used, for this task. (...)
    Download  
     
    Export citation  
     
    Bookmark   3 citations  
  2. Classification of Global Catastrophic Risks Connected with Artificial Intelligence.Alexey Turchin & David Denkenberger - 2020 - AI and Society 35 (1):147-163.
    A classification of the global catastrophic risks of AI is presented, along with a comprehensive list of previously identified risks. This classification allows the identification of several new risks. We show that at each level of AI’s intelligence power, separate types of possible catastrophes dominate. Our classification demonstrates that the field of AI risks is diverse, and includes many scenarios beyond the commonly discussed cases of a paperclip maximizer or robot-caused unemployment. Global catastrophic failure could happen at (...)
    Download  
    Translate
     
     
    Export citation  
     
    Bookmark   5 citations  
  3. Email Classification Using Artificial Neural Network.Ahmed Alghoul, Sara Al Ajrami, Ghada Al Jarousha, Ghayda Harb & Samy S. Abu-Naser - 2018 - International Journal of Academic Engineering Research (IJAER) 2 (11):8-14.
    Abstract: In recent years email has become one of the fastest and most economical means of communication. However increase of email users has resulted in the dramatic increase of spam emails during the past few years. Data mining -classification algorithms are used to categorize the email as spam or non-spam. Numerous email spam messages are marketable in nature but might similarly encompass camouflaged links that seem to be for acquainted websites but actually lead to phishing web sites or sites (...)
    Download  
     
    Export citation  
     
    Bookmark   8 citations  
  4. Causal Classification of Diseases.Andrej Poleev - 2020
    „Errors are the greatest obstacles to the progress of science; to correct such errors is of more practical value than to achieve new knowledge,“ asserted Eugen Bleuler. Basic error of several prevailing classification schemes of pathological conditions, as for example ICD-10, lies in confusing and mixing symptoms with diseases, what makes them unscientific. Considering the need to bring order into the chaos and light into terminological obscureness, I introduce the Causal classification of diseases originating from the notion of (...)
    Download  
    Translate
     
     
    Export citation  
     
    Bookmark   3 citations  
  5. Defeasible Classifications and Inferences From Definitions.Fabrizio Macagno & Douglas Walton - 2010 - Informal Logic 30 (1):34-61.
    We contend that it is possible to argue reasonably for and against arguments from classifications and definitions, provided they are seen as defeasible (subject to exceptions and critical questioning). Arguments from classification of the most common sorts are shown to be based on defeasible reasoning of various kinds represented by patterns of logical reasoning called defeasible argumentation schemes. We show how such schemes can be identified with heuristics, or short-cut solutions to a problem. We examine a variety of arguments (...)
    Download  
     
    Export citation  
     
    Bookmark   10 citations  
  6. Lemon Classification Using Deep Learning.Jawad Yousif AlZamily & Samy Salim Abu Naser - 2020 - International Journal of Academic Pedagogical Research (IJAPR) 3 (12):16-20.
    Abstract : Background: Vegetable agriculture is very important to human continued existence and remains a key driver of many economies worldwide, especially in underdeveloped and developing economies. Objectives: There is an increasing demand for food and cash crops, due to the increasing in world population and the challenges enforced by climate modifications, there is an urgent need to increase plant production while reducing costs. Methods: In this paper, Lemon classification approach is presented with a dataset that contains approximately 2,000 (...)
    Download  
     
    Export citation  
     
    Bookmark   1 citation  
  7. Banana Classification Using Deep Learning.Ahmed F. Al-Daour, Mohammed O. Al-Shawwa & Samy S. Abu-Naser - 2020 - International Journal of Academic Information Systems Research (IJAISR) 3 (12):6-11.
    Abstract: Banana, fruit of the genus Musa, of the family Musaceae, one of the most important fruit crops of the world. The banana is grown in the tropics, and, though it is most widely consumed in those regions, it is valued worldwide for its flavour, nutritional value, and availability throughout the year. Cavendish, or dessert, bananas are most commonly eaten fresh, though they may be fried or mashed and chilled in pies or puddings. They may also be used to flavour (...)
    Download  
     
    Export citation  
     
    Bookmark   1 citation  
  8. Glass Classification Using Artificial Neural Network.Mohmmad Jamal El-Khatib, Bassem S. Abu-Nasser & Samy S. Abu-Naser - 2019 - International Journal of Academic Pedagogical Research (IJAPR) 3 (23):25-31.
    As a type of evidence glass can be very useful contact trace material in a wide range of offences including burglaries and robberies, hit-and-run accidents, murders, assaults, ram-raids, criminal damage and thefts of and from motor vehicles. All of that offer the potential for glass fragments to be transferred from anything made of glass which breaks, to whoever or whatever was responsible. Variation in manufacture of glass allows considerable discrimination even with tiny fragments. In this study, we worked glass (...) and testing of artificial neural network model created by the JustNN. The aim of the study is help investigator in identifying the type of glass found in arena of the crime. The Neural Network model was trained and validated using the type of glass dataset. The accuracy of model in predicting the type of glass reached 96.7%. Thus neural network is suitable for predicating type of glasses. (shrink)
    Download  
     
    Export citation  
     
    Bookmark   6 citations  
  9. Classification Prediction of SBRCTs Cancers Using Artificial Neural Network.Remah Al-Massri, Yomna Al-Astel, Hanan Ziadia, Deyaa K. Mousa & Samy S. Abu-Naser - 2018 - International Journal of Academic Engineering Research (IJAER) 2 (11):1-7.
    Abstract: Small Blue Round Cell Tumors (SBRCTs) are a heterogeneous group of tumors that are difficult to diagnose because of overlapping morphologic, immunehistochemical, and clinical features. About two-thirds of EWSR1-negative SBRCTs are associated with CIC-DUX4-related fusions, whereas another small subset shows BCOR-CCNB3 X-chromosomal par acentric inversion. In this paper, we propose an ANN model to Classify and Predict SBRCTs Cancers. The accuracy of the classification reached 100%.
    Download  
     
    Export citation  
     
    Bookmark   7 citations  
  10. Avocado Classification Using Deep Learning.Mohammed N. Abu Alqumboz & Samy S. Abu-Naser - 2020 - International Journal of Academic Engineering Research (IJAER) 3 (12):30-34.
    Avocado is the fruit of the avocado tree, scientifically known as Persia Americana. This fruit is prized for its high nutrient value and is added to various dishes due to its good flavor and rich texture. It is the main ingredient in guacamole. These days, the avocado has become an incredibly popular food among health-conscious individuals. It’s often referred to as a superfood, which is not surprising given its health properties. Using a public dataset of 1,234 images of Avocado collected (...)
    Download  
     
    Export citation  
     
    Bookmark   1 citation  
  11. Potato Classification Using Deep Learning.Abeer A. Elsharif, Ibtesam M. Dheir, Alaa Soliman Abu Mettleq & Samy S. Abu-Naser - 2020 - International Journal of Academic Pedagogical Research (IJAPR) 3 (12):1-8.
    Abstract: Potatoes are edible tubers, available worldwide and all year long. They are relatively cheap to grow, rich in nutrients, and they can make a delicious treat. The humble potato has fallen in popularity in recent years, due to the interest in low-carb foods. However, the fiber, vitamins, minerals, and phytochemicals it provides can help ward off disease and benefit human health. They are an important staple food in many countries around the world. There are an estimated 200 varieties of (...)
    Download  
     
    Export citation  
     
    Bookmark   1 citation  
  12. Classification of Apple Fruits by Deep Learning.Mohammed O. Al-Shawwa & Samy S. Abu-Naser - 2020 - International Journal of Academic Engineering Research (IJAER) 3 (12):1-7.
    Abstract: Apple is a plant species that follows the apple genus, which is a fruit because it contains seeds of the pink family. It is one of the most fruit trees in terms of agriculture. The apple tree is small in length from 3 to 12 meters. Several recent studies have shown many health benefits of apples. It helps with the strengthening of the brain, heart, and stomach. It is used in the treatment of joint pain and limberness. It is (...)
    Download  
     
    Export citation  
     
    Bookmark   1 citation  
  13.  89
    A Classification System for Argumentation Schemes.Douglas Walton & Fabrizio Macagno - 2016 - Argument and Computation 6 (3):219-245.
    This paper explains the importance of classifying argumentation schemes, and outlines how schemes are being used in current research in artificial intelligence and computational linguistics on argument mining. It provides a survey of the literature on scheme classification. What are so far generally taken to represent a set of the most widely useful defeasible argumentation schemes are surveyed and explained systematically, including some that are difficult to classify. A new classification system covering these centrally important schemes is built.
    Download  
     
    Export citation  
     
    Bookmark   5 citations  
  14. Type of Tomato Classification Using Deep Learning.Mahmoud A. Alajrami & Samy S. Abu-Naser - 2020 - International Journal of Academic Pedagogical Research (IJAPR) 3 (12):21-25.
    Abstract: Tomatoes are part of the major crops in food security. Tomatoes are plants grown in temperate and hot regions of South American origin from Peru, and then spread to most countries of the world. Tomatoes contain a lot of vitamin C and mineral salts, and are recommended for people with constipation, diabetes and patients with heart and body diseases. Studies and scientific studies have proven the importance of eating tomato juice in reducing the activity of platelets in diabetics, which (...)
    Download  
     
    Export citation  
     
    Bookmark   1 citation  
  15. Plant Seedlings Classification Using Deep Learning.Belal A. M. Ashqar, Bassem S. Abu-Nasser & Samy S. Abu-Naser - 2019 - International Journal of Academic Information Systems Research (IJAISR) 3 (1):7-14.
    Agriculture is very important to human continued existence and remains a key driver of many economies worldwide, especially in underdeveloped and developing economies. There is an increasing demand for food and cash crops, due to the increasing in world population and the challenges enforced by climate modifications, there is an urgent need to increase plant production while reducing costs. Preceding instrument vision methods established for selective weeding have confronted with major challenges for trustworthy and precise weed recognition. In this paper, (...)
    Download  
     
    Export citation  
     
    Bookmark   6 citations  
  16. Interactive Classification and Practice in the Social Sciences.Matt L. Drabek - 2010 - Poroi 6 (2):62-80.
    This paper examines the ways in which social scientific discourse and classification interact with the objects of social scientific investigation. I examine this interaction in the context of the traditional philosophical project of demarcating the social sciences from the natural sciences. I begin by reviewing Ian Hacking’s work on interactive classification and argue that there are additional forms of interaction that must be treated.
    Download  
    Translate
     
     
    Export citation  
     
    Bookmark   2 citations  
  17.  67
    Classification of Animal Species Using Neural Network.Rand Suhail Abu Al-Araj, Shaima Khalil Abed, Ahmed Nabil Al-Ghoul & Samy S. Abu-Naser - 2020 - International Journal of Academic Engineering Research (IJAER) 4 (10):23-31.
    Abstract: Over 1.5 million living animal species have been described—of which around 1 million are insects—but it has been estimated there are over 7 million animal species in total. Animals range in length from 8.5 micrometres to 33.6 metres. In this paper an Artificial Neural Network (ANN) model, was developed and tested to predict animal species. There are a number of features that influence the classification of animal species. Such as the existence of hair/ feather, if the animal gives (...)
    Download  
     
    Export citation  
     
    Bookmark   2 citations  
  18.  61
    Evolving Efficient Classification Patterns in Lymphography Using EasyNN.Ahmed Suhail Jaber, Ahmed Khalil Humid, Mohammed Ahmed Hussein & Samy S. Abu-Naser - 2020 - International Journal of Academic Information Systems Research (IJAISR) 4 (9):66-73.
    A neural network exploits the non-linearity of a problem to define a set of desired inputs. Neural networks are important in realizing a better way for classification in machine learning and finds application in various fields such as data mining, pattern recognition, forensics etc. In this paper, our focus is to classify of patient records obtained from clinical data. Feature selection is a supervised method that attempts to select a subset of the predictor features based on the information gain. (...)
    Download  
     
    Export citation  
     
    Bookmark   2 citations  
  19. Type of Grapefruit Classification Using Deep Learning.Mohammed M. Abu-Saqer, Samy S. Abu-Naser & Mohammed O. Al-Shawwa - 2020 - International Journal of Academic Information Systems Research (IJAISR) 4 (1):1-5.
    Fruit has been recognized as a good source of vitamins and minerals, and for their role in preventing vitamin C and vitamin A deficiencies. People who eat fruit as part of an overall healthy diet generally have a reduced risk of chronic diseases. Fruit are important sources of many nutrients, including potassium, fiber, vitamin C and folate (folic acid). One of important types of fruit is Grapefruit . Grapefruit is a tropical citrus fruit known its sweet and somewhat sour taste. (...)
    Download  
     
    Export citation  
     
    Bookmark   3 citations  
  20. Phenomenological Psychopathology and Psychiatric Classification.Anthony Vincent Fernandez - 2019 - In Giovanni Stanghellini, Matthew Broome, Anthony Vincent Fernandez, Paolo Fusar-Poli, Andrea Raballo & René Rosfort (eds.), The Oxford Handbook of Phenomenological Psychopathology. Oxford, UK: pp. 1016-1030.
    In this chapter, I provide an overview of phenomenological approaches to psychiatric classification. My aim is to encourage and facilitate philosophical debate over the best ways to classify psychiatric disorders. First, I articulate phenomenological critiques of the dominant approach to classification and diagnosis—i.e., the operational approach employed in the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) and the International Classification of Diseases (ICD-10). Second, I describe the type or typification approach to psychiatric classification, which I (...)
    Download  
     
    Export citation  
     
    Bookmark   2 citations  
  21. Psychiatric Classification and Diagnosis. Delusions and Confabulations.Lisa Bortolotti - 2011 - Paradigmi (1):99-112.
    In psychiatry some disorders of cognition are distinguished from instances of normal cognitive functioning and from other disorders in virtue of their surface features rather than in virtue of the underlying mechanisms responsible for their occurrence. Aetiological considerations often cannot play a significant classificatory and diagnostic role, because there is no sufficient knowledge or consensus about the causal history of many psychiatric disorders. Moreover, it is not always possible to uniquely identify a pathological behaviour as the symptom of a certain (...)
    Download  
    Translate
     
     
    Export citation  
     
    Bookmark   3 citations  
  22. The Classification, Definition, and Ontology of Delusion.José Eduardo Porcher - 2016 - Revista Latinoamericana de Psicopatología Fundamental 19 (1):167-181.
    Although delusion is one of the central concepts of psychopathology, it stills eludes precise conceptualization. In this paper, I present certain basic issues concerning the classification and definition of delusion, as well as its ontological status. By examining these issues, I aim to shed light on the ambiguity of the clinical term ‘delusion’ and its extension, as well as provide clues as to why philosophers are increasingly joining the ranks of psychiatrists, psychologists, and neuroscientists in the effort to come (...)
    Download  
     
    Export citation  
     
    Bookmark   1 citation  
  23.  58
    Tumor Classification Using Artificial Neural Networks.Jamal Khamis El-Mahelawi, Jinan Usama Abu-Daqah, Rasha Ibrahim Abu-Latifa, Bassem S. Abu-Nasser & Samy S. Abu-Naser - 2020 - International Journal of Academic Engineering Research (IJAER) 4 (11):8-15.
    Abstract: Tumor is a group of diseases that involve abnormal increases in the number of cells, with the potential to invade or spread to other parts of the body. Not all tumors or lumps are cancerous; benign tumors are not classified as being cancer because they do not spread to other parts of the body. There are over 100 different known Tumors that affect humans. Tumors are often described by the body part that they originated in. However, some body parts (...)
    Download  
     
    Export citation  
     
    Bookmark   2 citations  
  24. Grape Type Classification Using Deep Learning.Hosni Qasim El-Mashharawi, Samy S. Abu-Naser, Izzeddin A. Alshawwa & Mohammed Elkahlout - 2020 - International Journal of Academic Engineering Research (IJAER) 3 (12):41-45.
    Abstract: A grape is a fruit, botanically a berry, of the deciduous woody vines of the flowering plant genus Vitis. it can be eaten fresh or they can be used for making jam, grape juice, jelly, grape seed extract, raisins, and grape seed oil. Grapes are a nonclimacteric type of fruit, generally occurring in clusters. Grapes are a type of fruit that grow in clusters of 15 to 300, and can be crimson, black, dark blue, yellow, green, orange, and pink. (...)
    Download  
     
    Export citation  
     
    Bookmark   1 citation  
  25. Natural Kinds, Psychiatric Classification and the History of the DSM.Jonathan Y. Tsou - 2016 - History of Psychiatry 27 (4):406-424.
    This paper addresses philosophical issues concerning whether mental disorders are natural kinds and how the DSM should classify mental disorders. I argue that some mental disorders (e.g., schizophrenia, depression) are natural kinds in the sense that they are natural classes constituted by a set of stable biological mechanisms. I subsequently argue that a theoretical and causal approach to classification would provide a superior method for classifying natural kinds than the purely descriptive approach adopted by the DSM since DSM-III. My (...)
    Download  
     
    Export citation  
     
    Bookmark   9 citations  
  26. Peach Type Classification Using Deep Learning.Mohammed I. El-Kahlout & Samy S. Abu-Naser - 2020 - International Journal of Academic Engineering Research (IJAER) 3 (12):35-40.
    Abstract: Peach, (Prunus persica), fruit tree of the rose family (Rosaceae), grown throughout the warmer temperate regions of both the Northern and Southern hemispheres. Peaches are widely eaten fresh and are also baked in pies and cobblers; canned peaches are a staple commodity in many regions. Yellow-fleshed varieties are especially rich in vitamin A. Peach trees are relatively short-lived as compared with some other fruit trees. In some regions orchards are replanted after 8 to 10 years, while in others trees (...)
    Download  
     
    Export citation  
     
    Bookmark   1 citation  
  27. On Triplet Classification of Concepts.Vladimir Kuznetsov - 1997 - Knowledge Organization 24 (3):163-175.
    The scheme for classifications of concepts is introduced. It has founded on the triplet model of concepts. In this model a concept is depicted by means of three kinds of knowledge: a concept base, a concept representing part and the linkage between them. The idea of triplet classifications of concepts is connected with a usage of various specifications of these knowledge kinds as classification criteria.
    Download  
    Translate
     
     
    Export citation  
     
    Bookmark   5 citations  
  28. Causation and Melanoma Classification.Brendan Clarke - 2011 - Theoretical Medicine and Bioethics 32 (1):19-32.
    In this article, I begin by giving a brief history of melanoma causation. I then discuss the current manner in which malignant melanoma is classified. In general, these systems of classification do not take account of the manner of tumour causation. Instead, they are based on phenomenological features of the tumour, such as size, spread, and morphology. I go on to suggest that misclassification of melanoma is a major problem in clinical practice. I therefore outline an alternative means of (...)
    Download  
     
    Export citation  
     
    Bookmark   4 citations  
  29.  59
    Grape Type Classification Using Deep Learning.Hosni Qasim El-Mashharawi, Samy S. Abu-Naser, Izzeddin A. Alshawwa & Mohammed Elkahlout - 2020 - International Journal of Academic Engineering Research (IJAER) 3 (12):41-45.
    Abstract: A grape is a fruit, botanically a berry, of the deciduous woody vines of the flowering plant genus Vitis. it can be eaten fresh or they can be used for making jam, grape juice, jelly, grape seed extract, raisins, and grape seed oil. Grapes are a nonclimacteric type of fruit, generally occurring in clusters. Grapes are a type of fruit that grow in clusters of 15 to 300, and can be crimson, black, dark blue, yellow, green, orange, and pink. (...)
    Download  
     
    Export citation  
     
    Bookmark   3 citations  
  30. Brentano's Classification of Mental Phenomena.Uriah Kriegel - 2017 - In U. Kriegel (ed.), Routledge Handbook of Franz Brentano and the Brentano School. London and New York: Routledge. pp. 97-102.
    In Chapter 3 of Book I of Psychology from an Empirical Standpoint, Brentano articulates what he takes to be the four most basic and central tasks of psychology. One of them is to discover the ‘fundamental classification’ of mental phenomena. Brentano attends to this task in Chapters 5-9 of Book II of the Psychology, reprinted (with appendices) in 1911 as a standalone book (Brentano 1911a). The classification is further developed in an essay entitled “A Survey of So-Called Sensory (...)
    Download  
     
    Export citation  
     
    Bookmark   2 citations  
  31. The Classification of the Sciences and Cross-Disciplinarity.Jaime Nubiola - 2005 - Transactions of the Charles S. Peirce Society 41 (2):271-282.
    In a world of ever growing specialization, the idea of a unity of science is commonly discarded, but cooperative work involving cross-disciplinary points of view is encouraged. The aim of this paper is to show with some textual support that Charles S. Peirce not only identified this paradoxical situation a century ago, but he also mapped out some paths for reaching a successful solution. A particular attention is paid to Peirce's classification of the sciences and to his conception of (...)
    Download  
     
    Export citation  
     
    Bookmark   1 citation  
  32. Letting Go of “Natural Kind”: Toward a Multidimensional Framework of Nonarbitrary Classification.David Ludwig - 2018 - Philosophy of Science 85 (1):31-52.
    This article uses the case study of ethnobiological classification to develop a positive and a negative thesis about the state of natural kind debates. On the one hand, I argue that current accounts of natural kinds can be integrated in a multidimensional framework that advances understanding of classificatory practices in ethnobiology. On the other hand, I argue that such a multidimensional framework does not leave any substantial work for the notion “natural kind” and that attempts to formulate a general (...)
    Download  
     
    Export citation  
     
    Bookmark   8 citations  
  33. How Non-Epistemic Values Can Be Epistemically Beneficial in Scientific Classification.Soohyun Ahn - 2020 - Studies in History and Philosophy of Science Part A 84:57-65.
    The boundaries of social categories are frequently altered to serve normative projects, such as social reform. Griffiths and Khalidi argue that the value-driven modification of categories diminishes the epistemic value of social categories. I argue that concerns over value-modified categories stem from problematic assumptions of the value-free ideal of science. Contrary to those concerns, non-epistemic value considerations can contribute to the epistemic improvement of a scientific category. For example, the early history of the category infantile autism shows how non-epistemic value (...)
    Download  
     
    Export citation  
     
    Bookmark   1 citation  
  34. Towards a Proteomics Meta-Classification.Anand Kumar & Barry Smith - 2004 - In IEEE Fourth Symposium on Bioinformatics and Bioengineering, Taichung, Taiwan. IEEE Press. pp. 419–427.
    that can serve as a foundation for more refined ontologies in the field of proteomics. Standard data sources classify proteins in terms of just one or two specific aspects. Thus SCOP (Structural Classification of Proteins) is described as classifying proteins on the basis of structural features; SWISSPROT annotates proteins on the basis of their structure and of parameters like post-translational modifications. Such data sources are connected to each other by pairwise term-to-term mappings. However, there are obstacles which stand in (...)
    Download  
     
    Export citation  
     
    Bookmark   4 citations  
  35. Classification of Approaches to Technological Resurrection.Alexey Turchin & Chernyakov Maxim - manuscript
    Abstract. Death seems to be a permanent event, but there is no actual proof of its irreversibility. Here we list all known ways to resurrect the dead that do not contradict our current scientific understanding of the world. While no method is currently possible, many of those listed here may become feasible with future technological development, and it may even be possible to act now to increase their probability. The most well-known such approach to technological resurrection is cryonics. Another method (...)
    Download  
     
    Export citation  
     
    Bookmark   1 citation  
  36. Revamping the Metaphysics of Ethnobiological Classification.David Ludwig - 2018 - Current Anthropology 59 (4):415-438.
    Ethnobiology has a long tradition of metaphysical debates about the “naturalness,” “objectivity”, “reality”, and “universality” of classifications. Especially the work of Brent Berlin has been influential in developing a “convergence metaphysics” that explains cross-cultural similarities of knowledge systems through shared recognition of objective discontinuities in nature. Despite its influence on the development of the field, convergence metaphysics has largely fallen out of favor as contemporary ethnobiologists tend to emphasize the locality and diversity of classificatory practices. The aim of this article (...)
    Download  
     
    Export citation  
     
    Bookmark   4 citations  
  37.  74
    An Ontology for Carcinoma Classification for Clinical Bioinformatics.Anand Kumar, Yum Lina Yip, Barry Smith, Dirk Marwede & Daniel Novotny - 2005 - Studies in Health Technology and Informatics 116 (1):635-640.
    There are a number of existing classifications and staging schemes for carcinomas, one of the most frequently used being the TNM classification. Such classifications represent classes of entities which exist at various anatomical levels of granularity. We argue that in order to apply such representations to the Electronic Health Records one needs sound ontologies which take into consideration the diversity of the domains which are involved in clinical bioinformatics. Here we outline a formal theory for addressing these issues in (...)
    Download  
     
    Export citation  
     
    Bookmark   1 citation  
  38. DSM-5 and Psychiatry's Second Revolution: Descriptive Vs. Theoretical Approaches to Psychiatric Classification.Jonathan Y. Tsou - 2015 - In Steeves Demazeux & Patrick Singy (eds.), The DSM-5 in Perspective: Philosophical Reflections on the Psychiatric Babel. Springer. pp. 43-62.
    A large part of the controversy surrounding the publication of DSM-5 stems from the possibility of replacing the purely descriptive approach to classification favored by the DSM since 1980. This paper examines the question of how mental disorders should be classified, focusing on the issue of whether the DSM should adopt a purely descriptive or theoretical approach. I argue that the DSM should replace its purely descriptive approach with a theoretical approach that integrates causal information into the DSM’s descriptive (...)
    Download  
     
    Export citation  
     
    Bookmark   8 citations  
  39. The Importance of History for Philosophy of Psychiatry: The Case of the DSM and Psychiatric Classification.Jonathan Y. Tsou - 2011 - Journal of the Philosophy of History 5 (3):446-470.
    Abstract Recently, some philosophers of psychiatry (viz., Rachel Cooper and Dominic Murphy) have analyzed the issue of psychiatric classification. This paper expands upon these analyses and seeks to demonstrate that a consideration of the history of the Diagnostic and Statistical Manual of Mental Disorders (DSM) can provide a rich and informative philosophical perspective for critically examining the issue of psychiatric classification. This case is intended to demonstrate the importance of history for philosophy of psychiatry, and more generally, the (...)
    Download  
     
    Export citation  
     
    Bookmark   11 citations  
  40. Classification, Kinds, Taxonomic Stability, and Conceptual Change.Jaipreet Mattu & Jacqueline Anne Sullivan - forthcoming - Aggression and Violent Behavior.
    Scientists represent their world, grouping and organizing phenomena into classes by means of concepts. Philosophers of science have historically been interested in the nature of these concepts, the criteria that inform their application and the nature of the kinds that the concepts individuate. They also have sought to understand whether and how different systems of classification are related and more recently, how investigative practices shape conceptual development and change. Our aim in this paper is to provide a critical overview (...)
    Download  
     
    Export citation  
     
    Bookmark  
  41. Locke's Theory of Classification.Judith Crane - 2003 - British Journal for the History of Philosophy 11 (2):249 – 259.
    Locke is often cited as a precursor to contemporary natural kind realism. However, careful attention to Locke’s arguments show that he was unequivocally a conventionalist about natural kinds. To the extent that contemporary natural kind realists see themselves as following Locke, they misunderstand what he was trying to do. Locke argues that natural kinds require either dubious metaphysical commitments (e.g., to substantial forms or universals), or a question-begging version of essentialism. Contemporary natural kind realists face a similar dilemma, and should (...)
    Download  
     
    Export citation  
     
    Bookmark   9 citations  
  42.  54
    Classification of Email Using ANN.Hareb Ghaydaa, A. Alghoul, Ajrami Ghada, Jarousha Ghaydaa & Daliah Kashef - 2016 - International Journal of Academic Engineering Research (IJAER) 2 (11):8-14.
    In recent years email has become one of the fastest and most economical means of communication. However increase of email users has resulted in the dramatic increase of spam emails during the past few years. Data mining -classification algorithms are used to categorize the email as spam or non-spam. Numerous email spam messages are marketable in nature but might similarly encompass camouflaged links that seem to be for acquainted websites but actually lead to phishing web sites or sites that (...)
    Download  
     
    Export citation  
     
    Bookmark  
  43. On the Classification of Śāntideva’s Ethics in the Bodhicaryāvatāra.Stephen E. Harris - 2015 - Philosophy East and West 65 (1):249-275.
    In this essay several challenges are raised to the project of classifying Śāntideva’s ethical reasoning given in his Bodhicaryāvatāra, or Guide to the Way of the Bodhisattva, as a species of ethical theory such as consequentialism or virtue ethics. One set of difficulties highlighted here arises because Śāntideva wrote this text to act as a manual of psychological transformation, and it is therefore often difficult to determine when his statements indicate his own ethical views. Further, even assuming we can identify (...)
    Download  
     
    Export citation  
     
    Bookmark   1 citation  
  44. Phenomenology and Dimensional Approaches to Psychiatric Research and Classification.Anthony Vincent Fernandez - 2019 - Philosophy, Psychiatry, and Psychology 26 (1):65-75.
    Contemporary psychiatry finds itself in the midst of a crisis of classification. The developments begun in the 1980s—with the third edition of the Diagnostic and Statistical Manual of Mental Disorders —successfully increased inter-rater reliability. However, these developments have done little to increase the predictive validity of our categories of disorder. A diagnosis based on DSM categories and criteria often fails to accurately anticipate course of illness or treatment response. In addition, there is little evidence that the DSM categories link (...)
    Download  
     
    Export citation  
     
    Bookmark   2 citations  
  45. On the Classification of Diseases.Benjamin Smart - 2014 - Theoretical Medicine and Bioethics 35 (4):251-269.
    Identifying the necessary and sufficient conditions for individuating and classifying diseases is a matter of great importance in the fields of law, ethics, epidemiology, and of course, medicine. In this paper, I first propose a means of achieving this goal, ensuring that no two distinct disease-types could correctly be ascribed to the same disease-token. I then posit a metaphysical ontology of diseases—that is, I give an account of what a disease is. This is essential to providing the most effective means (...)
    Download  
     
    Export citation  
     
    Bookmark   1 citation  
  46. Nonreductive Moral Classification and the Limits of Philosophy.Thomas V. Cunningham - 2014 - American Journal of Bioethics 14 (2):22-24.
    Download  
     
    Export citation  
     
    Bookmark   1 citation  
  47.  54
    A Framework for Protein Classification.Anand Kumar & Barry Smith - 2003 - In Proceedings of the 2003 German Conference on Bioinformatics, Vol. II. pp. 55-57.
    It is widely understood that protein functions can be exhaustively described in terms of no single parameter, whether this be amino acid sequence or the three-dimensional structure of the underlying protein molecule. This means that a number of different attributes must be used to create an ontology of protein functions. Certainly much of the required information is already stored in databases such as Swiss-Prot, Protein Data Bank, SCOP and MIPS. But the latter have been developed for different purposes and the (...)
    Download  
     
    Export citation  
     
    Bookmark   1 citation  
  48. Problem klasifikacije u filozofiji psihijatrije : slučaj psihopatije (Eng. The Problem of Classification in the Philosophy of Psychiatry: The Case of Psychopathy).Zdenka Brzović, Jelena Hodak, Luca Malatesti, Vesna Šendula-Jengić & Predrag Šustar - 2016 - Prolegomena 15 (1):21-41.
    The aim of this paper is to analyze, from a philosophical perspective, the scientific robustness of the construct of psychopathy as measured by the Psychopathy Checklist Revised that was developed by Robert Hare (1991; 2003). The scientific robustness and validity of classifications are topics of many debates in philosophy of science and philosophy of psychiatry more specifically. The main problem consists in establishing whether scientific classifications reflect natural kinds where the concept of a natural kind refers to the existence of (...)
    Download  
    Translate
     
     
    Export citation  
     
    Bookmark   3 citations  
  49. 10cubes and 3N3: Using Interactive Diagrams to Investigate Charles Peirces Classifications of Signs.Priscila Farias & João Queiroz - 2004 - Semiotica 2004 (151):41-63.
    This article presents some results of a research on computational strategies for the visualization of sign classification structures and sign processes. The focus of this research is the various classifications of signs described by Peirce. Two models are presented. One of them concerns specifically the 10-fold classification as described in the 1903 Syllabus (MS 540, EP 2: 289–299), while the other deals with the deep structure of Peirce’s various trichotomic classifications. The first is 10cubes, an interactive 3-D model (...)
    Download  
     
    Export citation  
     
    Bookmark   5 citations  
  50.  14
    Classification of Alzheimer’s Disease Using Traditional Classifiers with Pre-Trained CNN.Husam R. Almadhoun & Samy S. Abu-Naser - 2021 - International Journal of Academic Health and Medical Research (IJAHMR) 5 (4):17-21.
    Abstract: Alzheimer's disease (AD) is one of the most common types of dementia. Symptoms appear gradually and end with severe brain damage. People with Alzheimer's disease lose the abilities of knowledge, memory, language and learning. Recently, the classification and diagnosis of diseases using deep learning has emerged as an active topic covering a wide range of applications. This paper proposes examining abnormalities in brain structures and detecting cases of Alzheimer's disease especially in the early stages, using features derived from (...)
    Download  
     
    Export citation  
     
    Bookmark  
1 — 50 / 447