Medical Data Analysis and Processing using Explainable Artificial Intelligence (eBook, PDF)

Redaktion: Jena, Om Prakash; Kose, Utku; Panda, Mrutyunjaya

• Format: PDF

Produktbeschreibung

The text presents concepts of explainable artificial intelligence (XAI) in solving real world biomedical and healthcare problems.

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Produktdetails

• Verlag: Taylor & Francis
• Seitenzahl: 268
• Erscheinungstermin: 6. November 2023
• Englisch
• ISBN-13: 9781000983609
• Artikelnr.: 68992456

Autorenporträt

Dr. Om Prakash Jena is currently working as an Assistant Professor in the Department of Computer Science, Ravenshaw University, Cuttack, and Odisha, India. He has 11 years of teaching and research experience in the undergraduate and post-graduate levels. He has published several technical papers in international journals/conferences/edited book chapters of reputed publications. He is a member of IEEE, IETA, IAAC, IRED, IAENG, and WACAMLDS. His current research interest includes Database, Pattern Recognition, Cryptography, Network Security, Artificial Intelligence, Machine Learning, Soft Computing, Natural Language Processing, Data Science, Compiler Design, Data Analytics, and Machine Automation. He has many edited books, published by Wiley, CRC press, Taylor & Francis Bentham Publication into his credit and also the author of four textbooks under Kalyani Publisher. He also serve as a reviewer committee member and editor of many international journals. Dr. Mrutyunjaya Panda holds a Ph.D degree in Computer Science from Berhampur University. He obtained his Master in Engineering from Sambalpur University, MBA in HRM from IGNOU, New Delhi, and Bachelor in Engineering from Utkal University in 2002, 2009, 1997 respectively. He is having more than 20 years of teaching and research experience. He is presently working as Reader in P.G. Department of Computer Science and Applications, Utkal University, Bhubaneswar, Odisha, India. He is a member of MIR Labs (USA), KES (Australia), IAENG ( Hong Kong), ACEEE(I), IETE(I), CSI(I), ISTE(I). He has published about 70 papers in International and national journals and conferences. He has also published 7 book chapters to his credit. He has 2 text books and 3 edited books to his credit. He is a program committee member of various international conferences. He is acting as a reviewer of various international journals and conferences of repute. He is an Associate Editor of IJCINI Journal, IGI Global, USA and an Editorial board member of IJKESDP Journal of Inderscience, UK. He is also a Special issue Editor of International Journal of Computational Intelligence Studies (IJCIStudies), Inderscience, UK. His active area of research includes Data Mining, Image processing, Intrusion detection and prevention. Social networking, Mobile Communication, wireless sensor networks, Natural language processing, Internet of Things, Text Mining etc. Dr. Utku Kose received the B.S. degree in 2008 from computer education of Gazi University, Turkey as a faculty valedictorian. He received M.S. degree in 2010 from Afyon Kocatepe University, Turkey in the field of computer and D.S. / Ph. D. degree in 2017 from Selcuk University, Turkey in the field of computer engineering. Between 2009 and 2011, he has worked as a Research Assistant in Afyon Kocatepe University. Following, he has also worked as a Lecturer and Vocational School - Vice Director in Afyon Kocatepe University between 2011 and 2012, as a Lecturer and Research Center Director in Usak University between 2012 and 2017, and as an Assistant Professor in Suleyman Demirel University between 2017 and 2019. Currently, he is an Associate Professor in Suleyman Demirel University, Turkey. He has more than 100 publications including articles, authored and edited books, proceedings, and reports. He is also in editorial boards of many scientific journals and serves as one of the editors of the Biomedical and Robotics Healthcare book series by CRC Press. His research interest includes artificial intelligence, machine ethics, artificial intelligence safety, optimization, the chaos theory, distance education, e-learning, computer education, and computer science.

Inhaltsangabe

1. Explainable AI (XAI) Concepts and Theory. 2. Introduction to XAI in
Healthcare Application. 3. Machine Learning/Deep Learning Scalability
Models in Healthcare System. 4. Explainable AI-based Electronic Health
Records for Healthcare. 5. XAI Medical Data Exchanges and Data
Interoperability. 6. XAI-based Remote Care for Medical Data Analysis. 7.
Improving Patient Privacy and Security through XAI Models. 8. XAI for
Sentiment and Emotion Analysis for Patients. 9. Linguistic Knowledge of
Deep Neural Networks based on XAI. 10. Natural Language Processing and XAI
on Medical Data Processing. 11. Knowledge Representation Methods on Medical
Data using XAI. 12. XAI-based Trust and Interpretability in Classification.
13. Explainable Deep Bayesian Learning for Healthcare Applications. 14. XAI
Methods for Medical Internet of Things (MIoT) Data. 15. Algorithms, Tools,
Frameworks for Explainable AI on Medical Data. 16. Use cases and Future
aspects of XAI in Medical Data Analysis.