Swarm Intelligence and its Applications in Biomedical Informatics discusses Artificial Intelligence applications in medicine and biology, as well as challenges and opportunities presented in these arenas. It covers healthcare big data analytics, mobile health, personalized medicine, and clinical trial data management. The book shows how Artificial Intelligence can be used for early disease diagnosis prediction and prognosis, and offers health care case studies that demonstrate the application of AI and Machine Learning. Key Coverage: •Covers all major topics of swarm intelligence research and development such as novel based search methods and novel optimization algorithm: applications of swarm intelligence to management problems and swarm intelligence for real-world application. •Provides a unique insight into the complex problems of bioinformatics and the innovative solutions which make up ‘intelligent bioinformatics’. •Covers a wide range of topics on the role of Artificial Intelligence, Machine Learning, and Big Data for healthcare applications and deals with the ethical issues and concerns associated with it. •Explores applications in different areas of healthcare and highlights the current research. The book is designed as a reference text and aims primarily at advanced undergraduates and postgraduate students studying computer science and bioinformatics. Researchers and professionals will find this book useful.

The field of medical imaging seen rapid development over the last two decades and has consequently revolutionized the way in which modern medicine is practiced. Diseases and their symptoms are constantly changing therefore continuous updating is necessary for the data to be relevant. Diseases fall into different categories, even a small difference in symptoms may result in categorising it in a different group altogether. Thus analysing data accurately is of critical importance. This book concentrates on diagnosing diseases like cancer or tumor from different modalities of images. This book is divided into the following domains: Importance of big data in medical imaging, pre-processing, image registration, feature extraction, classification and retrieval. It is further supplemented by the medical analyst for a continuous treatment process. The book provides an automated system that could retrieve images based on user's interest to a point of providing decision support. It will help medical analysts to take informed decisions before planning treatment and surgery. It will also be useful to researchers who are working in problems involved in medical imaging.

The field of medical imaging seen rapid development over the last two decades and has consequently revolutionized the way in which modern medicine is practiced. Diseases and their symptoms are constantly changing therefore continuous updating is necessary for the data to be relevant. Diseases fall into different categories, even a small difference in symptoms may result in categorising it in a different group altogether. Thus analysing data accurately is of critical importance. This book concentrates on diagnosing diseases like cancer or tumor from different modalities of images. This book is divided into the following domains: Importance of big data in medical imaging, pre-processing, image registration, feature extraction, classification and retrieval. It is further supplemented by the medical analyst for a continuous treatment process. The book provides an automated system that could retrieve images based on user's interest to a point of providing decision support. It will help medical analysts to take informed decisions before planning treatment and surgery. It will also be useful to researchers who are working in problems involved in medical imaging.