Explainable Machine Learning for Multimedia Based Healthcare Applications
Editat de M. Shamim Hossain, Utku Kose, Deepak Guptaen Limba Engleză Hardback – 9 sep 2023
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Specificații
ISBN-13: 9783031380358
ISBN-10: 3031380355
Pagini: 233
Ilustrații: XIV, 233 p.
Dimensiuni: 155 x 235 mm
Greutate: 0.53 kg
Ediția:1st ed. 2023
Editura: Springer International Publishing
Colecția Springer
Locul publicării:Cham, Switzerland
ISBN-10: 3031380355
Pagini: 233
Ilustrații: XIV, 233 p.
Dimensiuni: 155 x 235 mm
Greutate: 0.53 kg
Ediția:1st ed. 2023
Editura: Springer International Publishing
Colecția Springer
Locul publicării:Cham, Switzerland
Cuprins
Foreword.- Preface.- Acknowledgement.- Table of Contents.- Chapter 1:.- Automatic Fetal Motion Detection from Trajectory of US Videos Based on YOLOv5 and LSTM.- Chapter 2:.- Explainable Machine Learning (XML) for Multimedia-based Healthcare Systems: Opportunities, Challenges, Ethical and Future Prospects.- Chapter 3:.- Ensemble deep learning architectures in bone cancer detection based on Medical Diagnosis in Explainable Artificial Intelligence.- Chapter 4:.- Digital dermatitis disease classification utilizing visual feature extraction and various machine learning techniques by explainable AI.- Chapter 5:.- Explainable Machine Learning in Healthcare.- Chapter 6:.- Explainable Artificial Intelligence with Scaling Techniques to Classify Breast Cancer Images.- Chapter 7:.- A Novel Approach of COVID -19 Estimation Using GIS and Kmeans Clustering: A Case of GEOAI.- Chapter 8:.- A Brief Review of Explainable Artificial Intelligence Reviews and Methods.- Chapter 9:.- Systematic Literature Review In Using Big Data Analytics And XAI Applications In Medical.- Chapter 10:.- Using Explainable Artificial Intelligence In Drug Discovery: A Theoretical Research.- Chapter 11:.- Application of Interpretable Artificial Intelligence enabled Cognitive Internet of Things for COVID-19 Pandemics.- Chapter 12:.- Remote Photoplethysmography: Digital Disruption in Health Vital Acquisition.
Notă biografică
Shamim Hossain is currently a Professor with the Department of Software Engineering, College of Computer and Information Sciences, King Saud University, Riyadh, Saudi Arabia. He is also an adjunct professor with the School of Electrical Engineering and Computer Science, University of Ottawa, ON, Canada. He received his Ph.D. in Electrical and Computer Engineering from the University of Ottawa, ON, Canada in 2009. His research interests include cloud networking, smart environment (smart city, smart health), AI, deep learning, edge computing, Internet of Things (IoT), multimedia for health care, and multimedia big data. He has authored and co-authored more than 335 publications including refereed journals (310+ SCI/ISI-Indexed papers, 180+ IEEE/ACM Transactions/Journal papers, 25+ ESI Highly Cited Papers, 2 Hot Papers), conference papers, books, and book chapters. Recently, he co-edited a book on “Connected Health in Smart Cities”, published by Springer. He has served as the co-chair, general chair, workshop chair, publication chair, and TPC in several IEEE and ACM conferences. He is the chair of the IEEE Special Interest Group on Artificial Intelligence (AI) for Health with the IEEE ComSoc eHealth Technical Committee. Currently, he is the Organizing Co-Chair of the Special Sessions with IEEE I2MTC 2022. He is also the Co-Chair of the 2nd IEEE GLOBECOM 2022 Workshop on Edge-AI and IoT for Connected Health. He is the Technical Program Co-Chair of ACM Multimedia 2023. He is the Symposium Co-Chair of Selected Areas in Communications (E-Health) with IEEE GLOBECOM 2024. Currently, he is the Chair of the Saudi Arabia Section of the Instrumentation and Measurement Society Chapter. He is a recipient of a number of awards, including the Best Conference Paper Award and the 2016 ACM Transactions on Multimedia Computing, Communications and Applications (TOMM) Nicolas D. Georganas Best Paper Award, the 2019 King Saud University Scientific Excellence Award (Research Quality), and the Research in Excellence Award from the College of Computer and Information Sciences (CCIS), King Saud University (3 times in a row). He is on the editorial board of the IEEE Transactions on Instrumentation and Measurement (TIM), IEEE Transactions on Multimedia (TMM), ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM), IEEE Multimedia, IEEE Network, IEEE Wireless Communications, Journal of Network and Computer Applications (Elsevier), International Journal of Multimedia Tools and Applications (Springer), and Games for Health Journal. He served as a Lead Guest Editor of more than 2 dozen of Special Issues (SIs) including the ACM Transactions on Internet Technology, ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM), IEEE Communications Magazine, IEEE Network, IEEE Transactions on Information Technology in Biomedicine (currently JBHI), IEEE Transactions on Cloud Computing, and Future Generation Computer Systems (Elsevier). He is a senior member of the IEEE and a Distinguished Member of the ACM. He is an IEEE Distinguished Lecturer (DL). He is a highly cited researcher and is listed as a Clarivate Analytics (Web of Science™) Highly Cited Researcher in Computer Science.
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 between2017 and 2019. Currently, he is an Associate Professor in Suleyman Demirel University, Turkey. He has more than 200 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 (CRC Press) and Computational Modeling Applications for Existential Risks (Elsevier) book series. His research interest includes artificial intelligence, machine ethics, artificial intelligence safety, biomedical applications, optimization, the chaos theory, distance education, e-learning, computer education, and computer science.
Dr. Deepak Gupta is an eminent academician; plays versatile roles and responsibilities juggling between lectures, research, publications, consultancy, community service, PhD and post-doctorate supervision etc. With 13 years of rich expertise in teaching and two years in industry; he focuses on rational and practical learning. He has contributed massive literature in the fields of Human-Computer Interaction, Intelligent Data Analysis, Nature-Inspired Computing, Machine Learning and Soft Computing. He is working as Assistant Professor at Maharaja Agrasen Institute of Technology (GGSIPU), Delhi, India. He has served as Editor-in-Chief, Guest Editor, Associate Editor in SCI and various other reputed journals (Elsevier, Springer, Wiley & MDPI). He has actively been part of various reputed International conferences. He is not only backed with a strong profile but his innovative ideas, research’s end-results and notion of implementation of technology in the medical field is by and large contributing to the society significantly. He is currently a Post-Doc researcher at University of Valladolid, Spain. He has completed his first Post-Doc from Inatel, Brazil, and Ph.D. from Dr. APJ Abdul Kalam Technical University. He has authored/Edited 47 books with National/International level publisher (Elsevier, Springer, Wiley, Katson). He has published 158 scientific research publications in reputed International Journals and Conferences including 79 SCI Indexed Journals of IEEE, Elsevier, Springer, Wiley and many more. He has also filed 3 patents. He is Editor-in-Chief of OA Journal-Computers and Quantum Computing and Applications (QCAA), Associate Editor of Expert Systems (Wiley), Intelligent Decision Technologies (IOS Press), Journal of Computational and Theoretical Nenoscience, Honorary Editor of ICSES Transactions on Image Processing and Pattern Recognition. He is also a series editor of "Elsevier Biomedical Engineering" (Elsevier), “Intelligent Biomedical Data Analysis” (De Gruyter, Germany), "Explainable AI (XAI) for Engineering Applications" (CRC Press) and "Computational Intelligence for Data Analysis" (Bentham Science). He is appointed as Consulting Editor at Elsevier. He is also associated with various professional bodies like IEEE, ISTE, IAENG, IACSIT, SCIEI, ICSES, UACEE, Internet Society, SMEI, IAOP, and IAOIP. Invited as a Faculty Resource Person/Session Chair/Reviewer/TPC member in different FDP, conferences and journals. He is the convener of ‘ICICC’ conference series. Dr. Gupta has great number of publication background, as considering Artificial Intelligence and biomedical applications. With his strong publication record in the target area, he is fitting very well into the book project. In the project, he will be responsible in author / contributor contacts in the context of Far East, and South America regions of the world.
Textul de pe ultima copertă
This book covers the latest research studies regarding Explainable Machine Learning used in multimedia-based healthcare applications. In this context, the content includes not only introductions for applied research efforts but also theoretical touches and discussions targeting open problems as well as future insights. In detail, a comprehensive topic coverage is ensured by focusing on remarkable healthcare problems solved with Artificial Intelligence. Because today’s conditions in medical data processing are often associated with multimedia, the book considers research studies with especially multimedia data processing.
Caracteristici
The book gives a very recent view on multimedia healthcare data and use of Explainable Machine Learning (XAI) The book provides both essential knowledge and technical details for understanding the target topic scope The book targets several important healthcare topics such as image-based diagnosis, COVID19, and drug discovery