Results for 'predictive medicine'

999 found
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  1. Medicine is Not Science: Guessing the Future, Predicting the Past.Clifford Miller - 2014 - Journal of Evaluation in Clinical Practice 20 (6):865–871.
    Abstract -/- Rationale, aims and objectives: Irregularity limits human ability to know, understand and predict. A better understanding of irregularity may improve the reliability of knowledge. -/- Method: Irregularity and its consequences for knowledge are considered. -/- Results: Reliable predictive empirical knowledge of the physical world has always been obtained by observation of regularities, without needing science or theory. Prediction from observational knowledge can remain reliable despite some theories based on it proving false. A naïve theory of irregularity is (...)
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  2. The Risk GP Model: The Standard Model of Prediction in Medicine.Jonathan Fuller & Luis J. Flores - 2015 - Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences 54:49-61.
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  3. Prediction in Epidemiology and Medicine.Jonathan Fuller, Alex Broadbent & Luis J. Flores - 2015 - Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences.
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  4.  45
    Introducing Knowledge-Based Medicine - Conference Presentation - Medicine is Not Science: Guessing the Future, Predicting the Past.Clifford Miller - 2014 - Conference Presentation Universidad Franscisco de Vitoria Person Centered Medicine July 2014; 07/2014.
    There is a middle ground of imperfect knowledge in fields like medicine and the social sciences. It stands between our day-to-day relatively certain knowledge obtained from ordinary basic observation of regularities in our world and our knowledge from well-validated theories in the physical sciences. -/- The latter enable reliable prediction a great deal of the time of the happening of events never before experienced. The former enable prediction only of what has happened before and beyond that of educated guesses (...)
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  5. Medicine is Not Science.Clifford Miller & Donald W. Miller - 2014 - European Journal for Person Centered Healthcare 2 (2):144-153.
    ABSTRACT: Abstract Most modern knowledge is not science. The physical sciences have successfully validated theories to infer they can be used universally to predict in previously unexperienced circumstances. According to the conventional conception of science such inferences are falsified by a single irregular outcome. And verification is by the scientific method which requires strict regularity of outcome and establishes cause and effect. -/- Medicine, medical research and many “soft” sciences are concerned with individual people in complex heterogeneous populations. These (...)
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  6. Precision Medicine and Big Data: The Application of an Ethics Framework for Big Data in Health and Research.G. Owen Schaefer, E. Shyong Tai & Shirley Sun - 2019 - Asian Bioethics Review 11 (3):275-288.
    As opposed to a ‘one size fits all’ approach, precision medicine uses relevant biological, medical, behavioural and environmental information about a person to further personalize their healthcare. This could mean better prediction of someone’s disease risk and more effective diagnosis and treatment if they have a condition. Big data allows for far more precision and tailoring than was ever before possible by linking together diverse datasets to reveal hitherto-unknown correlations and causal pathways. But it also raises ethical issues relating (...)
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  7. Mechanisms: What Are They Evidence for in Evidence-Based Medicine?Holly Andersen - 2012 - Journal of Evaluation in Clinical Practice 18 (5):992-999.
    Even though the evidence‐based medicine movement (EBM) labels mechanisms a low quality form of evidence, consideration of the mechanisms on which medicine relies, and the distinct roles that mechanisms might play in clinical practice, offers a number of insights into EBM itself. In this paper, I examine the connections between EBM and mechanisms from several angles. I diagnose what went wrong in two examples where mechanistic reasoning failed to generate accurate predictions for how a dysfunctional mechanism would respond (...)
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  8.  52
    ANN for Predicting DNA Lung Cancer.Wajeeh Abu Kashf, Nedal Okasha, Ashraf Sahyoun, Emal El-Rabi & Bastami Bashhar - 2017 - International Journal of Academic Pedagogical Research (IJAPR) 10 (2):6-13.
    Abstract: Lung cancer is the top reason of cancer-associated deaths globally. Surgery is the typical treatment for early-stage non-small cell lung cancer (NSCLC). Advancement in the knowledge of the biology of non-small cell lung cancer has shown molecular evidence used for systemic cancer therapy aiming metastatic disease, with a significant impact on patients’ overall survival (OS) and eminence of life. Though, a biopsy of overt metastases is an invasive technique restricted to assured positions and not effortlessly satisfactory in the clinic. (...)
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  9. The Idea of Mismatch in Evolutionary Medicine.Pierrick Bourrat & Paul Edmund Griffiths - manuscript
    Mismatch is a prominent concept in evolutionary medicine and a number of philosophers have published analyses of this concept. The word ‘mismatch’ has been used in a diversity of ways across a range of sciences, leading these authors to regard it as a vague concept in need of philosophical clarification. Here, in contrast, we concentrate on the use of mismatch in modelling and experimentation in evolutionary medicine. This reveals a rigorous theory of mismatch within which the term ‘mismatch’ (...)
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  10. Application of Double-Cusp Catastrophe Theory to the Physical Evolution of Qualia: Implications for Paradigm Shift in Medicine and Psychology.Richard L. Amoroso - 2004 - Anticipative and Predictive Models in Systems Science 1 (1):19-26.
    Seminal work intended to found a new field of integrative Noetic Science is summarized. Until now the philosophy of Biological Mechanism has ruled medicine and psychology. Penrose claims, AA scientific world-view which does not profoundly come to terms with the problem of conscious mind can have no serious pretensions of [email protected] A noetic action principle synonymous with the historic concept of élan vital is introduced as the basis of a Continuous State Conscious Universe (CSCU). The least unit of CSCU (...)
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  11. Should Aggregate Patient Preference Data Be Used to Make Decisions on Behalf of Unrepresented Patients?Nathaniel Sharadin - 2019 - AMA Journal of Ethics 21 (7):566-574.
    Patient preference predictors aim to solve the moral problem of making treatment decisions on behalf of incapacitated patients. This commentary on a case of an unrepresented patient at the end of life considers 3 related problems of such predictors: the problem of restricting the scope of inputs to the models (the “scope” problem), the problem of weighing inputs against one another (the “weight” problem), and the problem of multiple reasonable solutions to the scope and weight problems (the “multiple reasonable models” (...)
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  12. Limits of Trust in Medical AI.Joshua James Hatherley - 2020 - Journal of Medical Ethics 46 (7):478-481.
    Artificial intelligence is expected to revolutionise the practice of medicine. Recent advancements in the field of deep learning have demonstrated success in variety of clinical tasks: detecting diabetic retinopathy from images, predicting hospital readmissions, aiding in the discovery of new drugs, etc. AI’s progress in medicine, however, has led to concerns regarding the potential effects of this technology on relationships of trust in clinical practice. In this paper, I will argue that there is merit to these concerns, since (...)
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  13.  35
    Clinical Applications of Machine Learning Algorithms: Beyond the Black Box.David S. Watson, Jenny Krutzinna, Ian N. Bruce, Christopher E. M. Griffiths, Iain B. McInnes, Michael R. Barnes & Luciano Floridi - 2019 - British Medical Journal 364:I886.
    Machine learning algorithms may radically improve our ability to diagnose and treat disease. For moral, legal, and scientific reasons, it is essential that doctors and patients be able to understand and explain the predictions of these models. Scalable, customisable, and ethical solutions can be achieved by working together with relevant stakeholders, including patients, data scientists, and policy makers.
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  14. The Cybernetic Revolution and Historical Process.Leonid Grinin & Anton Grinin - 2015 - Social Evolution and History 14 (1):125-184.
    The article analyzes the technological shifts which took place in the second half of the twentieth and early twenty-first centuries and predict the main shifts in the next half a century. On the basis of the analysis of the latest achievements in medicine, bio- and nanotechnologies, robotics, ICT and other technological directions and also on the basis of the opportunities provided by the theory of production revolutions the authors present a detailed analysis of the latest production revolution which is (...)
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  15.  41
    Trust, Staking, and Expectations.Philip J. Nickel - 2009 - Journal for the Theory of Social Behaviour 39 (3):345-362.
    Trust is a kind of risky reliance on another person. Social scientists have offered two basic accounts of trust: predictive expectation accounts and staking accounts. Predictive expectation accounts identify trust with a judgment that performance is likely. Staking accounts identify trust with a judgment that reliance on the person's performance is worthwhile. I argue that these two views of trust are different, that the staking account is preferable to the predictive expectation account on grounds of intuitive adequacy (...)
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  16. The Cybernetic Revolution and the Forthcoming Epoch of Self-Regulating Systems.Leonud Grinin & Anton Grinin - 2016 - Moscow,Russia: "Uchitel" Publishing House.
    The monograph presents the ideas about the main changes that occurred in the development of technologies from the emergence of Homo sapiens till present time and outlines the prospects of their development in the next 30–60 years and in some respect until the end of the twenty-first century. What determines the transition of a society from one level of development to another? One of the most fundamental causes is the global technological transformations. Among all major technological breakthroughs in history the (...)
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  17. Translating Trial Results in Clinical Practice: The Risk GP Model.Jonathan Fuller & Luis J. Flores - 2016 - Journal of Cardiovascular Translational Research 9:167-168.
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  18. Diabetes Prediction Using Artificial Neural Network.Nesreen Samer El_Jerjawi & Samy S. Abu-Naser - 2018 - International Journal of Advanced Science and Technology 121:54-64.
    Diabetes is one of the most common diseases worldwide where a cure is not found for it yet. Annually it cost a lot of money to care for people with diabetes. Thus the most important issue is the prediction to be very accurate and to use a reliable method for that. One of these methods is using artificial intelligence systems and in particular is the use of Artificial Neural Networks (ANN). So in this paper, we used artificial neural networks to (...)
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  19. Will to Power.Joseph Tham - 2012 - The New Bioethics 18 (2):115-132.
    This paper analyzes the underlying tendencies and attitudes toward reproductive medicine borrowing the Nietzschean concepts of nihilism: “death of God” with secularization; “will to power” with reproductive liberty and technological power; and the race of “supermen” with transhumanism. Medical science has advanced in leaps and bounds. In some way, technical innovations have given us unprecedented power to manipulate the way we reproduce. The indiscriminant use of medical technology is backed by a warped notion of human freedom. With secularization in (...)
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  20.  11
    Simulating (Some) Individuals in a Connected World.Jenny Krutzinna - 2021 - Journal of Medical Ethics 47 (6):403-404.
    Braun explores the use of digital twin technology in medicine with a particular emphasis on the question of how such simulations can represent a person.1 In defining some first conditions for ethically justifiable forms of representation of digital twins, he argues that digital twins do not threaten an embodied person, as long as that person retains control over their simulated representation via dynamic consent, and ideally with the option to choose both form and usage of the simulation. His thoughtful (...)
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  21. A Very Brief Review of the Life and Work of Neuroscientist, Physician, Psychoanalyst, Inventor, Animal Rights Activist and Pioneer in Dolphins, Isolation Tanks and Psychedelics John C Lilly 1915-2001.Starks Michael - 2016 - In Michael Starks (ed.), Suicidal Utopian Delusions in the 21st Century: Philosophy, Human Nature and the Collapse of Civilization-- Articles and Reviews 2006-2017 2nd Edition Feb 2018. Michael Starks. pp. 577-580.
    Lilly was one of the greatest scientists and pioneers on the limits of human possibility but after his death a collective amnesia has descended and he is now almost forgotten. His Wiki is good but inevitably incomplete so here are a few missing details and viewpoints. Lilly was a generation (or more) ahead of his time. He is almost single-handedly responsible for the great interest in dolphins (which led to the Marine Mammal Protection Act in the USA and helped to (...)
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  22. Predictive Coding and Representationalism.Paweł Gładziejewski - 2016 - Synthese 193 (2).
    According to the predictive coding theory of cognition , brains are predictive machines that use perception and action to minimize prediction error, i.e. the discrepancy between bottom–up, externally-generated sensory signals and top–down, internally-generated sensory predictions. Many consider PCT to have an explanatory scope that is unparalleled in contemporary cognitive science and see in it a framework that could potentially provide us with a unified account of cognition. It is also commonly assumed that PCT is a representational theory of (...)
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  23. Contemporary Natural Philosophy and Philosophies - Part 1.Gordana Dodig-Crnkovic & Marcin J. Schroeder (eds.) - 2019 - Basel, Switzerland: MDPI.
    From the Philosophies journal program, one of the main aims of the journal is to help establish a new unity in diversity in human knowledge, which would include both “Wissen” (i.e., “Wissenschaft”) and “sc¯ıre” (i.e., “science”). As is known, “Wissenshaft” (the pursuit of knowledge, learning, and scholarship) is a broader concept of knowledge than “science”, as it involves all kinds of knowledge,including philosophy, and not exclusively knowledge in the form of directly testable explanations and predictions. The broader notion of scholarship (...)
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  24. Analytic Philosophy for Biomedical Research: The Imperative of Applying Yesterday's Timeless Messages to Today's Impasses.Sepehr Ehsani - 2020 - In P. Glauner & P. Plugmann (eds.), Innovative Technologies for Market Leadership - Investing in the Future. Springer. pp. 167-200.
    The mantra that "the best way to predict the future is to invent it" (attributed to the computer scientist Alan Kay) exemplifies some of the expectations from the technical and innovative sides of biomedical research at present. However, for technical advancements to make real impacts both on patient health and genuine scientific understanding, quite a number of lingering challenges facing the entire spectrum from protein biology all the way to randomized controlled trials should start to be overcome. The proposal in (...)
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  25. On Predicting.Fabrizio Cariani - forthcoming - Ergo: An Open Access Journal of Philosophy.
    I propose an account of the speech act of prediction that denies that the contents of prediction must be about the future and illuminates the relation between prediction and assertion. My account is a synthesis of two ideas: (i) that what is in the future in prediction is the time of discovery and (ii) that, as Benton and Turri recently argued, prediction is best characterized in terms of its constitutive norms.
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  26.  86
    Predictive Policing and the Ethics of Preemption.Daniel Susser - 2020 - In Ben Jones & Eduardo Mendieta (eds.), The Ethics of Policing: New Perspectives on Law Enforcement. New York: Nyu Press.
    The American justice system, from police departments to the courts, is increasingly turning to information technology for help identifying potential offenders, determining where, geographically, to allocate enforcement resources, assessing flight risk and the potential for recidivism amongst arrestees, and making other judgments about when, where, and how to manage crime. In particular, there is a focus on machine learning and other data analytics tools, which promise to accurately predict where crime will occur and who will perpetrate it. Activists and academics (...)
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  27. Me Medicine Vs. We Medicine: Reclaiming Biotechnology for the Common Good.Donna Dickenson - 2013 - New York, USA: Columbia University Press.
    Even in the increasingly individualized American medical system, advocates of 'personalized medicine' claim that healthcare isn't individualized enough. With the additional glamour of new biotechnologies such as genetic testing and pharmacogenetics behind it, 'Me Medicine'-- personalized or stratified medicine-- appears to its advocates as the inevitable and desirable way of the future. Drawing on an extensive evidence base, this book examines whether these claims are justified. It goes on to examine an alternative tradition rooted in communitarian ideals, (...)
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  28. Experience and Prediction: An Analysis of the Foundations and the Structure of Knowledge.Hans Reichenbach - 1938 - Chicago, IL, USA: University of Chicago Press.
    First published in 1949 expressly to introduce logical positivism to English speakers. Reichenbach, with Rudolph Carnap, founded logical positivism, a form of epistemofogy that privileged scientific over metaphysical truths.
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  29. Predicting Birth Weight Using Artificial Neural Network.Mohammed Al-Shawwa & Samy S. Abu-Naser - 2019 - International Journal of Academic Health and Medical Research (IJAHMR) 3 (1):9-14.
    In this research, an Artificial Neural Network (ANN) model was developed and tested to predict Birth Weight. A number of factors were identified that may affect birth weight. Factors such as smoke, race, age, weight (lbs) at last menstrual period, hypertension, uterine irritability, number of physician visits in 1st trimester, among others, as input variables for the ANN model. A model based on multi-layer concept topology was developed and trained using the data from some birth cases in hospitals. The evaluation (...)
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  30. Prediction of Whether Mushroom is Edible or Poisonous Using Back-Propagation Neural Network.Eyad Sameh Alkronz, Khaled A. Moghayer, Mohamad Meimeh, Mohannad Gazzaz, Bassem S. Abu-Nasser & Samy S. Abu-Naser - 2019 - International Journal of Academic and Applied Research (IJAAR) 3 (2):1-8.
    Abstract: Predication is an application of Artificial Neural Network (ANN). It is a supervised learning due to predefined input and output attributes. Multi-Layer ANN model is used for training, validating, and testing of the data. In this paper, Multi-Layer ANN model was used to train and test the mushroom dataset to predict whether it is edible or poisonous. The Mushrooms dataset was prepared for training, 8124 instances were used for the training. JustNN software was used to training and validating the (...)
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  31. Predicting Overall Car Performance Using Artificial Neural Network.Osama M. Al-Mubayyed, Bassem S. Abu-Nasser & Samy S. Abu-Naser - 2019 - International Journal of Academic and Applied Research (IJAAR) 3 (1):1-5.
    In this paper an Artificial Neural Network (ANN) model was used to help cars dealers recognize the many characteristics of cars, including manufacturers, their location and classification of cars according to several categories including: Buying, Maint, Doors, Persons, Lug_boot, Safety, and Overall. ANN was used in forecasting car acceptability. The results showed that ANN model was able to predict the car acceptability with 99.62 %. The factor of Safety has the most influence on car acceptability evaluation. Comparative study method is (...)
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  32. Predictive Coding Explains Binocular Rivalry: An Epistemological Review.Jakob Hohwy, Andreas Roepstorff & Karl Friston - 2008 - Cognition 108 (3):687-701.
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  33. Predicting Tumor Category Using Artificial Neural Networks.Ibrahim M. Nasser & Samy S. Abu-Naser - 2019 - International Journal of Academic Health and Medical Research (IJAHMR) 3 (2):1-7.
    In this paper an Artificial Neural Network (ANN) model, for predicting the category of a tumor was developed and tested. Taking patients’ tests, a number of information gained that influence the classification of the tumor. Such information as age, sex, histologic-type, degree-of-diffe, status of bone, bone-marrow, lung, pleura, peritoneum, liver, brain, skin, neck, supraclavicular, axillar, mediastinum, and abdominal. They were used as input variables for the ANN model. A model based on the Multilayer Perceptron Topology was established and trained using (...)
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  34. Predictive Processing and the Phenomenology of Time Consciousness: A Hierarchical Extension of Rick Grush’s Trajectory Estimation Model.Wanja Wiese - 2017 - Philosophy and Predictive Processing.
    This chapter explores to what extent some core ideas of predictive processing can be applied to the phenomenology of time consciousness. The focus is on the experienced continuity of consciously perceived, temporally extended phenomena (such as enduring processes and successions of events). The main claim is that the hierarchy of representations posited by hierarchical predictive processing models can contribute to a deepened understanding of the continuity of consciousness. Computationally, such models show that sequences of events can be represented (...)
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  35. Prediction Versus Accommodation in Economics.Robert Northcott - 2019 - Journal of Economic Methodology 26 (1):59-69.
    Should we insist on prediction, i.e. on correctly forecasting the future? Or can we rest content with accommodation, i.e. empirical success only with respect to the past? I apply general considerations about this issue to the case of economics. In particular, I examine various ways in which mere accommodation can be sufficient, in order to see whether those ways apply to economics. Two conclusions result. First, an entanglement thesis: the need for prediction is entangled with the methodological role of orthodox (...)
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  36.  35
    Precision Medicine, Data, and the Anthropology of Social Status.Hugh Desmond - 2021 - American Journal of Bioethics 21 (4):80-83.
    The success of precision medicine depends on obtaining large amounts of information about at-risk populations. However, getting consent is often difficult. Why? In this commentary I point to the differentials in social status involved. These differentials are inevitable once personal information is surrendered, but are particularly intense when the studied populations are socioeconomically or socioculturally disadvantaged and/or ethnically stigmatized groups. I suggest how the deep distrust of the latter groups can be partially justified as a lack of confidence that (...)
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  37. Causation, Prediction, and Search.Peter Spirtes, Clark Glymour, Scheines N. & Richard - 2000 - Mit Press: Cambridge.
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  38. Predictability Crisis in Early Universe Cosmology.Chris Smeenk - 2014 - Studies in History and Philosophy of Science Part B: Studies in History and Philosophy of Modern Physics 46 (1):122-133.
    Inflationary cosmology has been widely accepted due to its successful predictions: for a “generic” initial state, inflation produces a homogeneous, flat, bubble with an appropriate spectrum of density perturbations. However, the discovery that inflation is “generically eternal,” leading to a vast multiverse of inflationary bubbles with different low-energy physics, threatens to undermine this account. There is a “predictability crisis” in eternal inflation, because extracting predictions apparently requires a well-defined measure over the multiverse. This has led to discussions of anthropic predictions (...)
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  39. Prediction, Authority, and Entitlement in Shared Activity.Abraham Sesshu Roth - 2014 - Noûs 48 (4):626-652.
    Shared activity is often simply willed into existence by individuals. This poses a problem. Philosophical reflection suggests that shared activity involves a distinctive, interlocking structure of intentions. But it is not obvious how one can form the intention necessary for shared activity without settling what fellow participants will do and thereby compromising their agency and autonomy. One response to this problem suggests that an individual can have the requisite intention if she makes the appropriate predictions about fellow participants. I argue (...)
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  40. Direct Perception and the Predictive Mind.Zoe Drayson - 2018 - Philosophical Studies 175 (12):3145-3164.
    Predictive approaches to the mind claim that perception, cognition, and action can be understood in terms of a single framework: a hierarchy of Bayesian models employing the computational strategy of predictive coding. Proponents of this view disagree, however, over the extent to which perception is direct on the predictive approach. I argue that we can resolve these disagreements by identifying three distinct notions of perceptual directness: psychological, metaphysical, and epistemological. I propose that perception is plausibly construed as (...)
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  41. Assertion, Knowledge and Predictions.Matthew A. Benton - 2012 - Analysis 72 (1):102-105.
    John N. Williams (1994) and Matthew Weiner (2005) invoke predictions in order to undermine the normative relevance of knowledge for assertions; in particular, Weiner argues, predictions are important counterexamples to the Knowledge Account of Assertion (KAA). I argue here that they are not true counterexamples at all, a point that can be agreed upon even by those who reject KAA.
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  42. Noise, Uncertainty, and Interest: Predictive Coding and Cognitive Penetration.Jona Vance & Dustin Stokes - 2017 - Consciousness and Cognition 47:86-98.
    This paper concerns how extant theorists of predictive coding conceptualize and explain possible instances of cognitive penetration. §I offers brief clarification of the predictive coding framework and relevant mechanisms, and a brief characterization of cognitive penetration and some challenges that come with defining it. §II develops more precise ways that the predictive coding framework can explain, and of course thereby allow for, genuine top-down causal effects on perceptual experience, of the kind discussed in the context of cognitive (...)
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  43. Energy Efficiency Prediction Using Artificial Neural Network.Ahmed J. Khalil, Alaa M. Barhoom, Bassem S. Abu-Nasser, Musleh M. Musleh & Samy S. Abu-Naser - 2019 - International Journal of Academic Pedagogical Research (IJAPR) 3 (9):1-7.
    Buildings energy consumption is growing gradually and put away around 40% of total energy use. Predicting heating and cooling loads of a building in the initial phase of the design to find out optimal solutions amongst different designs is very important, as ell as in the operating phase after the building has been finished for efficient energy. In this study, an artificial neural network model was designed and developed for predicting heating and cooling loads of a building based on a (...)
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  44. ANN Model for Predicting Protein Localization Sites in Cells.Mohammed Nafez Abu Samra, Bilal Ezz El-Din Abed, Hossam Abdel Nasser Zaqout & Samy S. Abu-Naser - 2020 - International Journal of Academic and Applied Research (IJAAR) 4 (9):43-50.
    To automate examination of massive amounts of sequence data for biological function, it is important to computerize interpretation based on empirical knowledge of sequence-function relationships. For this purpose, we have been constructing an Artificial Neural Network (ANN) by organizing various experimental and computational observations as a collection ANN models. Here we propose an ANN model which utilizes the Dataset for UCI Machine Learning Repository, for predicting localization sites of proteins. We collected data for 336 proteins with known localization sites and (...)
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  45. A Theory of Predictive Dissonance: Predictive Processing Presents a New Take on Cognitive Dissonance.Roope Oskari Kaaronen - 2018 - Frontiers in Psychology 9.
    This article is a comparative study between predictive processing (PP, or predictive coding) and cognitive dissonance (CD) theory. The theory of CD, one of the most influential and extensively studied theories in social psychology, is shown to be highly compatible with recent developments in PP. This is particularly evident in the notion that both theories deal with strategies to reduce perceived error signals. However, reasons exist to update the theory of CD to one of “predictive dissonance.” First, (...)
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  46. Modularity and the Predictive Mind.Zoe Drayson - 2017 - T. Metzinger and W. Weise, (Eds), Philosophy and Predictive Processing.
    Modular approaches to the architecture of the mind claim that some mental mechanisms, such as sensory input processes, operate in special-purpose subsystems that are functionally independent from the rest of the mind. This assumption of modularity seems to be in tension with recent claims that the mind has a predictive architecture. Predictive approaches propose that both sensory processing and higher-level processing are part of the same Bayesian information-processing hierarchy, with no clear boundary between perception and cognition. Furthermore, it (...)
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  47. What? Now. Predictive Coding and Enculturation.Richard Menary - 2015 - In Thomas Metzinger & Jennifer M. Windt (eds.), Open Mind. M.I.T. Press.
    Regina Fabry has proposed an intriguing marriage of enculturated cognition and predictive processing. I raise some questions for whether this marriage will work and warn against expecting too much from the predictive processing framework. Furthermore I argue that the predictive processes at a sub-personal level cannot be driving the innovations at a social level that lead to enculturated cognitive systems, like those explored in my target paper.
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  48. Medicine and the Individual: Is Phenomenology the Answer?Tania L. Gergel - 2012 - Journal of Evaluation in Clinical Practice 18 (5):1102-1109.
    The issue of how to incorporate the individual's first‐hand experience of illness into broader medical understanding is a major question in medical theory and practice. In a philosophical context, phenomenology, with its emphasis on the subject's perception of phenomena as the basis for knowledge and its questioning of naturalism, seems an obvious candidate for addressing these issues. This is a review of current phenomenological approaches to medicine, looking at what has motivated this philosophical approach, the main problems it faces (...)
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  49.  75
    Renewing Medicine’s Basic Concepts: On Ambiguity.Joel Michael Reynolds - 2018 - Philosophy, Ethics, and Humanities in Medicine 13 (1):8.
    In this paper, I argue that the concept of normality in medical research and clinical practice is inextricable from the concept of ambiguity. I make this argument in the context of Edmund Pellegrino's call for a renewed reflection on medicine’s basic concepts and by drawing on work in critical disability studies concerning Deafness and body integrity identity disorder. If medical practitioners and philosophers of medicine wish to improve their understanding of the meaning of medicine as well as (...)
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  50. Artificial Neural Network for Predicting Car Performance Using JNN.Awni Ahmed Al-Mobayed, Youssef Mahmoud Al-Madhoun, Mohammed Nasser Al-Shuwaikh & Samy S. Abu-Naser - 2020 - International Journal of Engineering and Information Systems (IJEAIS) 4 (9):139-145.
    In this paper an Artificial Neural Network (ANN) model was used to help cars dealers recognize the many characteristics of cars, including manufacturers, their location and classification of cars according to several categories including: Buying, Maint, Doors, Persons, Lug_boot, Safety, and Overall. ANN was used in forecasting car acceptability. The results showed that ANN model was able to predict the car acceptability with 99.12 %. The factor of Safety has the most influence on car acceptability evaluation. Comparative study method is (...)
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