Advancing Healthcare through Decision Intelligence: Machine Learning, Robotics, and Analytics in Biomedical Informatics demonstrates real-world applications of decision intelligence - specifically machine learning, robotics, and analytics - to drive innovation and improvements in healthcare delivery and outcomes. The book provides a comprehensive overview of the latest developments in decision intelligence technologies, and offers a practical resource that can help navigate through the complex landscape of healthcare decision-making. In 5 themes Advancing Healthcare through Decision Intelligence: Machine Learning, Robotics, and Analytics in Biomedical Informatics focuses on the use of data analytics aad management techniques in healthcare to improve decision-making and healthcare outcomes, on the use of robotics, robots and genomics to improve biomedical informatics, on the use of genomics, clinical decision support systems (CDSS), machine learning, and deep learning to improve precision medicine and personalized treatment and on the ethical implications of using artificial intelligence (AI) in healthcare, ensuring trust in the technology, and making sure that it can be explained and understood by all stakeholders. This book is a valuable resource for health professionals, scientists and researchers, health practitioners, students, and all those who wish to broaden their knowledge in the allied field.
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Dr. Somen Dey obtained his (PhD) degree in the area of Operations Management and Manufacturing Strategy from the Department of Industrial and Management Engineering, Indian Institute of Technology Kanpur, India. His primary research interests include operations management, supply chain management, organization, and manufacturing strategy, strategic information systems (IS), production planning and control, operations research and optimization techniques. He also has secondary research interests in data mining, machine learning algorithms, knowledge discovery database (KDD) applications in manufacturing and production planning and control. He was the recipient of the Best Track Paper Award in Operations Management in 7th Annual Conference on Industrial Engineering and Operations Management, IEOM, April (11th–13th) 2017, Rabat Morocco.
Vidyapati Kumar is a Ph.D. Research Scholar in the Department of Mechanical Engineering at the Indian Institute of Technology Kharagpur, specializing in AI-driven Rehabilitation Robotics, Biomechatronics, and Assistive Prosthetic Systems. His research focuses on intelligent prosthetic control, wearable biomedical devices, and advanced sensor fusion techniques, including electromyography (EMG), inertial measurement units (IMU), and force-sensitive resistors (FSR), aimed at enhancing mobility and improving quality of life for individuals with physical impairments.
He holds a Master’s degree in Production Engineering from Jadavpur University and a Bachelor’s degree in Mechanical Engineering from the West Bengal University of Technology (WBUT). Prior to his doctoral studies, he served as a GATE Faculty member for Unacademy and worked as a Project Assistant at the Central Institute of Mining and Fuel Research.
Vidyapati Kumar has published multiple papers in high-impact SCI and Scopus-indexed journals. His research interests include prosthetic design, medical artificial intelligence, explainability methods in AI/ML such as SHAP and LIME, optimization, and multi-criteria decision-making. He actively pursues interdisciplinary collaborations in biomedical robotics, wearable assistive devices, and advanced healthcare technologies.
Advancing Healthcare through Decision Intelligence: Machine Learning, Robotics, and Analytics in Biomedical Informatics demonstrates real-world applications of decision intelligence - specifically machine learning, robotics, and analytics - to drive innovation and improvements in healthcare delivery and outcomes. The book provides a comprehensive overview of the latest developments in decision intelligence technologies, and offers a practical resource that can help navigate through the complex landscape of healthcare decision-making. In 5 themes Advancing Healthcare through Decision Intelligence: Machine Learning, Robotics, and Analytics in Biomedical Informatics focuses on the use of data analytics aad management techniques in healthcare to improve decision-making and healthcare outcomes, on the use of robotics, robots and genomics to improve biomedical informatics, on the use of genomics, clinical decision support systems (CDSS), machine learning, and deep learning to improve precision medicine and personalized treatment and on the ethical implications of using artificial intelligence (AI) in healthcare, ensuring trust in the technology, and making sure that it can be explained and understood by all stakeholders. This book is a valuable resource for health professionals, scientists and researchers, health practitioners, students, and all those who wish to broaden their knowledge in the allied field.
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