Biomedical Data Analysis and Processing Using Explainable (XAI) and Responsive Artificial Intelligence (RAI)
Herausgegeben:Khamparia, Aditya; Gupta, Deepak; Khanna, Ashish; Balas, Valentina E.
Biomedical Data Analysis and Processing Using Explainable (XAI) and Responsive Artificial Intelligence (RAI)
Herausgegeben:Khamparia, Aditya; Gupta, Deepak; Khanna, Ashish; Balas, Valentina E.
- Broschiertes Buch
- Merkliste
- Auf die Merkliste
- Bewerten Bewerten
- Teilen
- Produkt teilen
- Produkterinnerung
- Produkterinnerung
The book discusses Explainable (XAI) and Responsive Artificial Intelligence (RAI) for biomedical and healthcare applications. It will discuss the advantages in dealing with big and complex data by using explainable AI concepts in the field of biomedical sciences. The book explains both positive as well as negative findings obtained by explainable AI techniques. It features real time experiences by physicians and medical staff for applied deep learning based solutions. The book will be extremely useful for researchers and practitioners in advancing their studies.
Andere Kunden interessierten sich auch für
- Biomedical Data Analysis and Processing Using Explainable (XAI) and Responsive Artificial Intelligence (RAI)132,99 €
- Explainable Artificial Intelligence for Cyber Security171,19 €
- Explainable Artificial Intelligence for Cyber Security117,99 €
- Tin-Chih Toly ChenExplainable Artificial Intelligence (XAI) in Manufacturing37,99 €
- Explainable Edge AI: A Futuristic Computing Perspective161,99 €
- Explainable Edge AI: A Futuristic Computing Perspective161,99 €
- Mohammad Amir Khusru AkhtarTowards Ethical and Socially Responsible Explainable AI147,99 €
-
-
-
The book discusses Explainable (XAI) and Responsive Artificial Intelligence (RAI) for biomedical and healthcare applications. It will discuss the advantages in dealing with big and complex data by using explainable AI concepts in the field of biomedical sciences. The book explains both positive as well as negative findings obtained by explainable AI techniques. It features real time experiences by physicians and medical staff for applied deep learning based solutions. The book will be extremely useful for researchers and practitioners in advancing their studies.
Produktdetails
- Produktdetails
- Intelligent Systems Reference Library 222
- Verlag: Springer / Springer Nature Singapore / Springer, Berlin
- Artikelnr. des Verlages: 978-981-19-1478-2
- 1st ed. 2022
- Seitenzahl: 156
- Erscheinungstermin: 11. April 2023
- Englisch
- Abmessung: 235mm x 155mm x 9mm
- Gewicht: 276g
- ISBN-13: 9789811914782
- ISBN-10: 9811914788
- Artikelnr.: 67619608
- Intelligent Systems Reference Library 222
- Verlag: Springer / Springer Nature Singapore / Springer, Berlin
- Artikelnr. des Verlages: 978-981-19-1478-2
- 1st ed. 2022
- Seitenzahl: 156
- Erscheinungstermin: 11. April 2023
- Englisch
- Abmessung: 235mm x 155mm x 9mm
- Gewicht: 276g
- ISBN-13: 9789811914782
- ISBN-10: 9811914788
- Artikelnr.: 67619608
Dr. Aditya Khamparia has expertise in Teaching, Entrepreneurship, and Research & Development of 8 years. He received his Ph.D. degree from Lovely Professional University, Punjab in May 2018. He has completed his M. Tech. from VIT University and B. Tech. from RGPV, Bhopal. He has completed his PDF from UNIFOR, Brazil. He has around 65 research papers along with book chapters including more than 15 papers in SCI indexed Journals with cumulative impact factor of above 50 to his credit. Additionally, He has authored, edited and editing 5 books. Furthermore, he has served the research field as a Keynote Speaker/Session Chair/Reviewer/TPC member/ Guest Editor and many more positions in various conferences and journals. His research interest includes machine learning, deep learning, educational technologies, computer vision. Deepak Gupta received a B.Tech. degree in 2006 from the Guru Gobind Singh Indraprastha University, Delhi, India. He received M.E. degree in 2010 from Delhi Technological University, India and Ph. D. degree in 2017 from Dr. APJ Abdul Kalam Technical University (AKTU), Lucknow, India. He has completed his Post-Doc from National Institute of Telecommunications (Inatel), Brazil in 2018. He has co-authored more than 183 journal articles including 145 SCI papers and 44 conference articles. He has authored/edited 50 books, published by IEEE-Wiley, Elsevier, Springer, Wiley, CRC Press, DeGruyter and Katsons. He has filled four Indian patents. He is convener of ICICC, ICDAM, DoSCI & ICCCN Springer conferences series. Currently he is Associate Editor of Alexandria Journal (Elsevier), Expert Systems (Wiley), and Intelligent Decision Technologies (IOS Press). He is the recipient of 2021 IEEE System Council Best Paper Award. He have been featured in the list of top 2% scientist/researcher database in the world [Table-S7-singleyr-2019]. He is also working towards promoting Startups and also serving as a Startup Consultant. He is also a series editor of ¿Elsevier Biomedical Engineering¿ at Academic Press, Elsevier, ¿Intelligent Biomedical Data Analysis¿ at De Gruyter, Germany, ¿Explainable AI (XAI) for Engineering Applications¿ at CRC Press. He is appointed as Consulting Editor at Elsevier. Dr. Ashish Khanna [M¿19, SM¿20] has expertise in Teaching, Entrepreneurship, and Research & Development with specialization in Computer Science Engineering Subjects. He received his Ph.D. degree from National Institute of Technology, Kurukshetra in March 2017. He has completed his PDF from Internet of Things Lab at Inatel, Brazil. He completed his M. Tech. in 2009 and B. Tech. from GGSIPU, Delhi in 2004. He is part of AD Scientific World ranking report as a leading researcher. He has around 160 accepted and published research papers and book chapters in reputed SCI, Scopus journals, conferences and reputed book series including 82 papers accepted and published in SCI indexed Journals and Cumulative Impact Factor of above 300. He also has 5 published Patents to his credit. Additionally, He has co-authored, edited and currently editing around 37 books. He is also serving as Series Editor in publishing houses like De Gruyter (Germany) of "Intelligent Biomedical Data Analysis" series, Elsevier of ¿Intelligent Biomedical Data Analysis¿ and CRC Press of ¿Intelligent Techniques in Distributed Systems: Principles and Applications¿. He is also acting as a consulting editor for Elsevier. His research interests include Distributed Systems and its variants (MANET, FANET, VANET, IoT), Machine learning, NLP and many more. He is the recipient of the 2021 IEEE System Council Best Paper Award. He is serving as convener/ General chair in some springer international conferences series like ICICC, ICDAM, DoSCI, ICCCN and many more. He is a senior IEEE member (SMIEEE) and an ACM member too. He has played a key role in promoting and initiating several startups and is also a startup consultant. He has also played the key role in promoting Smart India Hackathon at MAIT. He initiated the first ever of its kind event in India ``WHERE STARTUP MEETS INVESTOR '' in collaboration with Universal Inovator and SIIF SSCBS, DU under the banner of ICICC-2020 international conference. First time a Research based conference was conducted along with a Startup funding event. He also played a key role in India's first conference on Patents (ICIIP-2021) in association with UI and IGDTUW Delhi. He is serving as a consultant and mentor to some of the successful startups. He is also a key originator of Bhavya Publication house and Universal Inovator an Indian Research Lab. Google scholar index is 4000. Valentina E. Balas is currently Full Professor in the Department of Automatics and Applied Software at the Faculty of Engineering, ¿Aurel Vlaicü University of Arad, Romania. She holds a Ph.D. Cum Laude, in Applied Electronics and Telecommunications from Polytechnic University of Timisoara. Dr. Balas is author of more than 400 research papers in refereed journals and International Conferences. Her research interests are in Intelligent Systems, Fuzzy Control, Soft Computing, Smart Sensors, Information Fusion, Modeling and Simulation. She is the Editor-in Chief to International Journal of Advanced Intelligence Paradigms (IJAIP) and to International Journal of Computational Systems Engineering (IJCSysE), member in Editorial Board member of several national and international journals and is evaluator expert for national, international projects and PhD Thesis. Dr. Balas is the director of Intelligent Systems Research Centre in Aurel Vlaicu University of Arad and Director of the Department of International Relations, Programs and Projects in the same university. She served as General Chair of the International Workshop Soft Computing and Applications (SOFA) in nine editions organized in the interval 2005-2020 and held in Romania and Hungary. Dr. Balas participated in many international conferences as Organizer, Honorary Chair, Session Chair, member in Steering, Advisory or International Program Committees and Keynote Speaker. Recently she was working in a national project with EU funding support: BioCell-NanoART = Novel Bio-inspired Cellular Nano-Architectures - For Digital Integrated Circuits, 3M Euro from National Authority for Scientific Research and Innovation. She is a member of European Society for Fuzzy Logic and Technology (EUSFLAT), member of Society for Industrial and Applied Mathematics (SIAM) and a Senior Member IEEE, member in Technical Committee ¿ Fuzzy Systems (IEEE Computational Intelligence Society), chair of the Task Force 14 in Technical Committee ¿ Emergent Technologies (IEEE CIS), member in Technical Committee ¿ Soft Computing (IEEE SMCS). Dr. Balas was past Vice-president (responsible with Awards) of IFSA - International Fuzzy Systems Association Council (2013-2015), is a Joint Secretary of the Governing Council of Forum for Interdisciplinary Mathematics (FIM), - A Multidisciplinary Academic Body, India and recipient of the "Tudor Tanasescu" Prize from the Romanian Academy for contributions in the field of soft computing methods (2019).
Optimal Boosting Label Weighting Extreme Learning Machine for Mental Disorder Prediction and Classification.- Modeling of Explainable Artificial Intelligence with Correlation based Feature Selection Approach for Biomedical Data Analysis.- Explainable machine learning model for diagnosis of Parkinson disorder.- Explainable Artificial Intelligence with Metaheuristic Feature Selection Technique for Biomedical Data Classification.- Explainable AI in Neural Networks using Shapley Values.- Design of Multimodal Fusion based Deep Learning Approach for COVID-19 Diagnosis using Chest X-Ray Images.
Optimal Boosting Label Weighting Extreme Learning Machine for Mental Disorder Prediction and Classification.- Modeling of Explainable Artificial Intelligence with Correlation based Feature Selection Approach for Biomedical Data Analysis.- Explainable machine learning model for diagnosis of Parkinson disorder.- Explainable Artificial Intelligence with Metaheuristic Feature Selection Technique for Biomedical Data Classification.- Explainable AI in Neural Networks using Shapley Values.- Design of Multimodal Fusion based Deep Learning Approach for COVID-19 Diagnosis using Chest X-Ray Images.