Explainable Machine Learning for Multimedia Based Healthcare Applications

lt;b>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(TM)) 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 betw

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.