Explainable Artificial Intelligence for Biomedical and Healthcare Applications
Idioma: inglés
Editorial: Taylor and Francis Ltd, GB, 2024
- Tapa dura
- Nuevo

Librería: Rarewaves.com USA, London, London, Reino UnidoRarewaves.com USA
Vendedor de AbeBooks desde 11 de junio de 2025
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EUR 256,75
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This reference text helps us understand how the concepts of explainable artificial intelligence (XAI) are used in the medical and healthcare sectors. The text discusses medical robotic systems using XAI and physical devices having autonomous behaviors for medical operations. It explores the usage of XAI for analyzing different types of unique data sets for medical image analysis, medical image registration, medical data synthesis, and information discovery. It covers important topics including XAI for biometric security, genomics, and medical disease diagnosis.This book. Provides an excellent foundation for the core concepts and principles of explainable AI in biomedical and healthcare applications. Covers explainable AI for robotics and autonomous systems. Discusses usage of explainable AI in medical image analysis, medical image registration, and medical data synthesis. Examines biometrics security-assisted applications and their integration using explainable AI.The text will be useful for graduate students, professionals, and academic researchers in diverse areas such as electrical engineering, electronics and communication engineering, biomedical engineering, and computer science.…
N° de ref. del artículo LU-9781032114897
- Título
- Explainable Artificial Intelligence for Biomedical and Healthcare Applications
- Autor
- Aditya Khamparia
- Editorial
- Taylor and Francis Ltd, GB
- Año de publicación
- 2024
- Estado
- New
- Encuadernación
- Hardback
- Idioma
- inglés
- ISBN 10
- 1032114894
- ISBN 13
- 9781032114897
- Peso del artículo
- 720 gramos
This reference text helps us understand how the concepts of explainable artificial intelligence (XAI) are used in the medical and healthcare sectors. The text discusses medical robotic systems using XAI and physical devices having autonomous behaviors for medical operations. It explores the usage of XAI for analyzing different types of unique data sets for medical image analysis, medical image registration, medical data synthesis, and information discovery. It covers important topics including XAI for biometric security, genomics, and medical disease diagnosis.
This book:
• Provides an excellent foundation for the core concepts and principles of explainable AI in biomedical and healthcare applications.
• Covers explainable AI for robotics and autonomous systems.
• Discusses usage of explainable AI in medical image analysis, medical image registration, and medical data synthesis.
• Examines biometrics security-assisted applications and their integration using explainable AI.
The text will be useful for graduate students, professionals, and academic researchers in diverse areas such as electrical engineering, electronics and communication engineering, biomedical engineering, and computer science.
“Sinopsis” puede pertenecer a otra edición de este título.
Acerca del autor
Aditya Khamparia has more than ten years of experience in teaching, entrepreneurship, and research & development. He is currently an Assistant Professor and Coordinator of the Department of Computer Science, Babasaheb Bhimrao Ambedkar University, Satellite Centre, Amethi, India. He earned his PhD from Lovely Professional University, Punjab, in May 2018. He completed his MTech from VIT University and BTech from RGPV, Bhopal. He completed his PDF from UNIFOR, Brazil. He has more than 100 research papers along with book chapters including more than 20 papers in SCI-indexed journals with a cumulative impact factor of above 50 to his credit. Additionally, He has authored and edited 10 books. He has been featured in the list of top 2% scientist/researcher databases worldwide. In India, he has been ranked 1 as a researcher in the field of healthcare applications (as per Google Scholar citations). 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 interests include machine learning, deep learning, educational technologies, and computer vision.
Deepak Gupta earned a BTech degree in 2006 from the Guru Gobind Singh Indraprastha University, Delhi, India. He earned an ME degree in 2010 from Delhi Technological University, India, and PhD in 2017 from Dr APJ Abdul Kalam Technical University (AKTU), Lucknow, India. He completed his Post-Doc from the National Institute of Telecommunications (Inatel), Brazil, in 2018. He has co-authored more than 207 journal articles, including 168 SCI papers and 45 conference articles. He has authored/edited 60 books, published by IEEE-Wiley, Elsevier, Springer, Wiley, CRC Press, DeGruyter, and Katsons. He has filled four Indian patents. He is the convener of the ICICC, ICDAM, ICCCN, ICIIP, and DoSCI Springer conferences series. He is Associate Editor of Computer & Electrical Engineering, Expert Systems, Alexandria Engineering Journal, and Intelligent Decision Technologies. He is the recipient of the 2021 IEEE System Council Best Paper Award. He has been featured in the list of top 2% scientist/researcher databases worldwide. In India, he has been ranked 1 as a researcher in the field Copyright Material – Provided by Taylor & Francis of healthcare applications (as per Google Scholar citations) and ranked #78 in India among Top Scientists 2022 by Research .co m. He is also working toward 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, and "Explainable AI (XAI) for Engineering Applications" at CRC Press. He is appointed as Consulting Editor at Elsevier. He accomplished productive collaborative research with grants of approximately $144,000 from various international funding agencies, and he is Co-PI in an International Indo-Russian Joint project of Rs 1.31CR from the Department of Science and Technology.
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