Advances in Computational Intelligence for Health Informatics and Computer-Aided Diagnosis: Methods, Applications, and Tools

This book provides a comprehensive overview of the intersection of computational intelligence, health informatics, and computer-aided diagnosis (CAD). The book explores and highlights the latest advancements, methodologies, applications, and tools in these fields.

Advances in Computational Intelligence for Health Informatics and Computer-Aided Diagnosis: Methods, Applications, and Tools covers a broad spectrum of computational intelligence approaches, from basic concepts to advanced methodologies. The focus on health informatics reflects the book’s commitment to researching data integration, privacy issues, and interoperability issues that are crucial in today’s healthcare landscape. The book’s core is its in-depth examination of CAD systems, which encompasses numerous healthcare sectors and underlines the technological complexity involved in building accurate and efficient diagnostic tools. Some of the other key areas covered include: medical imaging analysis, disease identification and diagnosis, and drug research and development. It also provides case studies that demonstrate how computational intelligence methods are applied in real-world healthcare scenarios, giving readers a practical understanding of the subject matter. The authors then discuss future trends and directions in computational intelligence for health informatics.

The book is designed to serve as a guide to for academics, professionals, and students who are curious about the challenges of integrating contemporary computational approaches into medical diagnostics and decision support.

Dr. A. Malini is an Associate Professor at Vellore Institute of Technology, Chennai, Tamil Nadu. She has 20+ years of teaching experience, and obtained her doctoral degree from Anna University, Chennai. She is a Lifetime member of Computer Society of India. She has been a mentor and won smart India Hackathon 2022 held at NIT Assam. Her research interest includes software Engineering, Software Testing, Mobile Application development, Green Computing, Internet of Things, Artificial Intelligence and Machine Learning.

Dr. Surbhi B. Khan is currently working in the School of Science, Engineering and Environment at University of Salford, United Kingdom. She has earned Project Management Professional Certification from the Project Management Institute, USA. She also enjoys an adjunct professor position from Chandigarh University, India and has more than 13 years of academic and teaching experience. Her area of interests is Sentiment Analysis, Deep Learning/Machine learning, and Data science in healthcare.

Dr. S. Kayalvizhi is an accomplished academician and researcher, currently serving as an Assistant Professor (Senior Grade) in the Department of Electronics and Communication Engineering at SRM University. She earned a Ph.D. in Compressive Sensing and Signal Processing from the SRM Institute of Science and Technology in 2021. With over 20 years of academic experience, she has made significant contributions to the fields of signal processing, machine learning, and healthcare technologies. Her areas of expertise include deep learning, IoT-based healthcare systems, and AI-driven disease prediction models.

Professor Mo Saraee holds a chair in Data Science, the head of Computer Science and Software Engineering and is the programme leader of the MSc Data Science and MSc IoT (Internet of Things) Programmes at the University of Salford, Manchester, UK, where he also received his Ph.D. His research focuses on Data Science, Machine Learning, Data & Text Mining, NLP, Big Data, and Medical Informatics, addressing multi-disciplinary, cross-school topics with transformative impact, benefiting local communities, dedication to action through real-world application of research including developing and integrating innovative data mining approaches to improve human health, in collaboration with both Salford City Council and the NHS.