The book reviews the transformative impact of robotics and generative AI technologies on healthcare. It covers the engineering principles and key technologies that support modern healthcare robotics. By explaining the core components and their functions, the book provides readers with a deep understanding of how these technologies contribute to medical innovations. It also explores the basics of generative AI, focusing on its underlying models and practical applications, including its role in transforming diagnostics. The book explains the applications of generative AI in diagnostic precision, and in improving patient care.
Furthermore, the practical aspects of integrating these technologies into healthcare settings are addressed, including the challenges and opportunities involved. It discusses the ethical considerations surrounding the use of robotics and AI, such as data privacy, bias, and regulatory compliance. The final chapters deal with future developments, emerging trends, and potential innovations in the field, offering a forward-looking perspective on how robotics and AI will continue to shape the future of healthcare.
Key Features:
- Deals with the convergence of robotics and generative AI in healthcare
- Provides a holistic coverage of the technical, clinical, and ethical aspects of robotics and generative AI in healthcare
- Reviews the core technologies behind healthcare robotics
- Addresses important ethical considerations and regulatory challenges associated with implementing robotics and AI in healthcare
- Explores emerging trends and future innovations in robotics and AI, offering readers insights into what is next in the field
Deepika Kumar is an Associate Professor and Head of Department, Computer Science & Engineering at Bharati Vidyapeeth's College of Engineering, New Delhi. She has a PhD in the area of Machine Learning and Bioinformatics. She has more than 16 years of teaching experience. Her research interests are Machine Learning, Artificial Intelligence and Bioinformatics. She has been granted two patents and published more than 30 research papers in various SCI, SCIE, Scopus indexed journals and conferences. She has also published a book Dimensionality Reduction, Feature Extraction, and Manifold in Machine Learning. She received "Best Researcher Award" for consecutively four years for her contribution in research at Bharati Vidyapeeth's College of Engineering, New Delhi.
Gargi Mishra has a Master's degree from the Indian Institute of Technology, Roorkee, and a PhD in Machine Learning from GGSIP University, New Delhi. With over 15 years of experience in teaching, technical writing, and research, she is currently an Associate Professor at Bharati Vidyapeeth's College of Engineering, New Delhi, in the Department of Computer Science and Engineering. Her research interests include artificial intelligence, machine learning, and computer vision.
Jude D Hemanth is a Full Professor in the Department of ECE at Karunya University, Coimbatore, India. He holds a B.E. in ECE, an M.E. in Communication Systems, and a Ph.D. in Computational Intelligence and Image Processing. He has authored over 280 research papers in reputed journals and conferences, with a cumulative impact factor exceeding 520, and has published 49 edited books with leading publishers. Dr. Hemanth serves as Associate Editor for several SCIE-indexed journals, including IEEE JBHI, IEEE Transactions on ITS, Soft Computing (Springer), IET Image Processing, and Heliyon (Elsevier). He is the series editor for the "Biomedical Engineering" series (Elsevier) and "Robotics and Healthcare" (CRC Press), and a board member for the ASTI series (Springer). He has led and collaborated on funded research projects from the UK (GCRF), CSIR, and DST (India), and is affiliated as a Research Scientist with labs in Argentina, Brazil, Tunisia, Romania, and Spain. Dr. Hemanth has delivered 200+ keynote talks worldwide and is a certified NVIDIA Deep Learning instructor.
