Machine Learning and Deep Learning Techniques for Medical Science

This book explores the integration of machine learning and deep learning in healthcare, focusing on enhancing diagnostic accuracy, developing predictive tools, and addressing challenges through case studies and recent innovations.

Machine Learning and Deep Learning Techniques for Medical Science explores the integration of machine learning (ML) and deep learning (DL) algorithms within the healthcare sector. The primary aim of the book is to enhance the efficiency of medical professionals, including doctors and radiologists, by significantly reducing the time required for analyzing, predicting, and diagnosing various medical conditions with high accuracy.

The book delves into the rapid growth of ML and DL applications across various fields, particularly in medical science. It covers essential aspects of developing and implementing these technologies to create effective prediction tools and improve diagnostic processes. Contributors discuss current trends, innovations, challenges, and solutions in intelligent system-based disease diagnosis, providing a comprehensive overview of the subject matter.

Additionally, the text addresses the mathematical foundations necessary for developing new medical models and examines the intersection of ML and DL with artificial intelligence (AI) tools. Topics include drug discovery, neuroscience, and the use of multiple imaging modalities for diagnosis. This book serves as a valuable resource for students and researchers in computer science, biomedical engineering, and healthcare, as well as professionals seeking to understand the impact of advanced technologies in the medical field.