Artificial Intelligence and Cloud Computing Applications in Biomedical Engineering

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Madhusudhan H S (Vidyavardhaka College of Engineering, India) Punit Gupta (Pandit DeenDayal Energy University, India)

Artificial Intelligence and Cloud Computing Applications in Biomedical Engineering

Madhusudhan H S (Vidyavardhaka College of Engineering, India), Punit Gupta (Pandit DeenDayal Energy University, India), Pradeep Singh Rawat , Dinesh Kumar Saini (Texas Tech University, USA)

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English

Auerbach
15 September 2025

Regulation of medicines & medical devices; Medical imaging; Biomedical engineering; WAP (wireless) technology; Artificial intelligence

Biomedical engineering is undergoing a transformation because of AI, which is allowing creative solutions that enhance patient outcomes, diagnosis, treatment planning, and healthcare delivery. Artificial Intelligence and Cloud Computing Applications in Biomedical Engineering examines the salient characteristics of AI in biomedical engineering, highlighting its practical applications and new directions. Highlights of the book include:

Genome sequence and visualization The role of AI and cloud in detection of diseases Nature-inspired algorithms for disease detection Frameworks for disease classification

With a focus on designing AI techniques for disease detection, the book explores the role of AI in biomedical engineering. It discusses how machine learning (ML) and deep learning (DL) are at the heart of AI applications in biomedical engineering. ML algorithms, particularly those based on neural networks, enable computers to learn from large datasets, identify patterns, and make predictions or decisions without explicit programming, and implementing ML algorithms is a focus of the book. Another focus is on DL, a subset of ML, and how it uses multi-layered neural networks to achieve high accuracy in such complex tasks as image and speech recognition. Biomedical engineering generates massive amounts of data from medical imaging, genomic sequencing, wearable devices, electronic health records (EHR), and other sources. The book also discusses AI-driven big data analytics, which allows researchers and clinicians to derive from data meaningful insights, aiding in early disease detection, personalized treatment plans, and patient monitoring.

Edited by: Madhusudhan H S (Vidyavardhaka College of Engineering India), Punit Gupta (Pandit DeenDayal Energy University, India), Pradeep Singh Rawat, Dinesh Kumar Saini (Texas Tech University, USA)
Imprint: Auerbach
Country of Publication: United Kingdom
Dimensions: Height: 234mm, Width: 156mm,
ISBN: 9781041015260
ISBN 10: 1041015267
Pages: 264
Publication Date: 15 September 2025
Audience: College/higher education , Primary
Format: Hardback
Publisher's Status: Forthcoming

Dr. Madhusudhan H S an associate professor in the Department of Computer Science and Engineering at Vidyavardhaka College of Engineering, Mysuru, India. Dr. Punit Gupta is an associate professor in the department of Computer and Communication Engineering at Manipal University Jaipur, India. Dr. Pradeep Singh Rawat is an assistant professor with the Department of Computer Science and Engineering at DIT University, Dehradun, India. Dr. Dinesh Kumar Saini is a full professor at the School of Computing and Information Technology, Manipal University