Artificial Intelligence (AI) offers tremendous opportunities to transform healthcare by reducing human error, supporting medical professionals, and providing continuous patient services. With ongoing advancements, AI has demonstrated significant potential in medical imaging, such as interpreting X-rays, scans, and other diagnostics, as well as assisting in disease identification and treatment planning. Beyond clinical applications, AI is streamlining healthcare operations—from managing patient interactions and answering queries to analyzing population-level health data and predicting emerging health trends.
The book, Artificial Intelligence in Biomedical Sciences and Healthcare, will serve as a comprehensive collection of current research on AI and its applications across diverse areas of biochemical and medical sciences. It will not only present recent advances in AI but also introduce the foundational concepts of biomedical sciences and machine learning, enabling students and professionals to better grasp these interdisciplinary fields.
Furthermore, the book will address real-world challenges in healthcare—such as diagnostics, treatment, and disease management—and illustrate how AI-driven techniques can provide innovative solutions. This volume aims to serve as a valuable reference for students, researchers, academicians, and professionals engaged in biomedical sciences and AI.
Table of Contents:
1. Role of artificial intelligence in healthcare and biomedical science 2. Applications of artificial intelligence in healthcare 3. Artificial intelligence in the treatment and diagnosis of infectious diseases 4. The role of artificial intelligence in diabetes: A review of recent advances 5. Artificial intelligence in gynecology 6. Role of AI in gastroenterology: Prevention, diagnostics, and treatment 7. Artificial intelligence in drug delivery 8. Artificial intelligence in genomics 9. Trends and challenges in the field of medical sciences using AI 10. A survey of clinical decision support systems
About the Author :
Dr. Imran Khan is currently working as an Assistant Professor at Department of Computer Science and Engineering, Harcourt Butler Technical University, Kanpur, India. He completed his Ph.D. from Jamia Millia Islamia, New Delhi, India. He did his Master’s in Computer Applications from Aligarh Muslim University, Aligarh, India. He has more than 13 years of both industry as well teaching experience. He worked as Senior Data Scientist at Crysp Analytics, Noida, India. Also, he worked as an Assistant Professor at BVICAM, New Delhi. He published more than 40 research papers in various Journals and Conferences. His area of research is Artificial Intelligence, Machine Learning, Deep Learning and Data Science.
Dr. Santosh Kumar is currently working as an Associate Professor & Head at Department of Chemistry, Harcourt Butler Technical University Kanpur, India. He also served as Research Professor in Department of Organic and Nano System Engineering, Division of Chemical Engineering, Konkuk University, Seoul, South Korea. Dr. Kumar received his B.Sc, M.Sc. in Chemistry and D. Phil. in Organic Chemistry from University of Allahabad, India. He worked as a Research Associate (CSIR) at Department of Chemistry, Motilal Nehru National Institute of Technology, Allahabad, India. He was awarded CAS-TWAS Postdoctoral fellowship in 2008 and worked in Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun, China. Later he joined as a KU Brain Pool Professor and researcher at the Konkuk University, Seoul, South Korea (2010-2013). He was awarded FCT Postdoctoral Fellowship 2012; worked in Chemistry Centre, University of Coimbra, Coimbra, Portugal (2013-2017). During his career, Dr. Kumar has published a more than 111 research papers, edited 5 books and 21 book chapters, attended and participated in local and international workshops, and conferences. He also served as a member of different organizing committees and an editorial board member and reviewer at a number of scientific journals. Current research interest involves source apportionment of chemical modification, optical and biological properties of chitosan biopolymer for biomedical applications, hydrogel, aerogel, nanomaterials, drug & gene delivery.
