Within Artificial Intelligence, programmers use the terms "Black Box" or "White Box". Explainable AI (XAI) is a "white box" model, and is artificial intelligence in which the results of the solution can be understood by humans. It contrasts with the concept of the "black box" in machine learning where the inner workings of the models are harder to understand and don't provide an estimate of the importance of each feature on the model predictions, nor explain how the different features interact to arrive at a specific decision.
Medical Decision Support Systems (MDSS) are computer-based programs that analyse data within a patient's healthcare records to provide questions, prompts or reminders to assist clinicians at the point of care, for example, it may requests some of the patient's data (height, weight, age, sex etc.) or symptoms (headache, rash, dizziness, breathlessness) or current treatment (drug(s) and dosage) and in response, propose a set of appropriate diagnoses or treatment plans.
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Agbotiname Lucky Imoize is a lecturer in the Department of Electrical and Electronics Engineering at the University of Lagos, Nigeria and a research scholar at Ruhr University Bochum, Germany. He is a Fulbright fellow, a senior member of the IEEE, and a registered engineer. He has published over 90 articles and conference papers, two edited textbooks, and five book chapters. His research interests are 6G wireless communication, artificial intelligence, and the Internet of Things.
Jude Hemanth is a professor at Karunya University, Coimbatore, India. He has delivered more than 100 keynote talks and invited lectures at international conferences and workshops, and has authored more than 100 research papers and 27 edited books. His research areas include computational intelligence and image processing.
Dinh-Thuan Do is a research scientist in the Department of Electrical Engineering, University of Colorado Denver, USA. He won a Golden Globe Award from the Vietnam Ministry of Science and Technology in 2015. He has published over 200 journal and conference papers, one textbook, two edited books and eight book chapters. His research interests include signal processing in wireless communications networks, full-duplex transmission, and energy harvesting.
Samarendra Nath Sur is an assistant professor in the Department of Electronics & Communication Engineering at Sikkim Manipal Institute of Technology, India. His research interests include wireless communication, signal processing, and remote sensing. He has published more than 77 SCI/Scopus indexed international journal and conference papers, four edited textbooks, and five book chapters. He is a senior member of the IEEE and associate member of the Institution of Engineers (India) (IEI).
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Etat : New. KlappentextThis edited book gives insights into the deployment, application, management, and benefits of explainable artificial intelligence (XAI) in medical decision support systems (MDSS). The book discusses XAI-based analytics for . N° de réf. du vendeur 715344698
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