Mukesh Roy

This book explores a wide range of methods for advanced solutions in the field of oncology. It explores the transformative role of AI in advancing cancer care, focusing on its applications in drug discovery, surgical progress, and digital twin technology. The book provides an in-depth analysis of AI's impact on various cancers, including breast, colorectal, brain, and others, and highlights its potential to enhance early detection, accurate diagnosis, and personalized treatment. The book will investigate the development and optimization of AI algorithms to achieve high accuracy in detecting malignant cells at different stages. The technologies encompass machine learning techniques to identify patterns in medical imaging, natural language processing to evaluate patient histories, and deep learning models to forecast treatment outcomes. Specific methodologies such as supervised and unsupervised learning models, convolutional neural networks for image analysis, and reinforcement learning for adaptive treatment strategies are provided. The utilization of case studies and real-world examples in cancer care will demonstrate every approach, enabling readers to gain a practical understanding of how these technologies might be implemented.

The book Artificial Intelligence for Healthcare: Machine Learning and Diagnostics explores how AI and machine learning are reshaping healthcare, focusing on diagnosis, patient care, and treatment across various specialties. It covers AI applications in fields such as cardiovascular care, orthopedics, emergency medicine, ENT, and remote patient monitoring. Additionally, the book discusses AI’s transformative role in brain tumor surgery, dentistry, and elder care, showcasing its power to personalize therapies, predict outcomes, and enhance outpatient efficiency. Key chapters examine AI in pathology, specifically in image analysis and digital pathology, and its expanding influence in maternal and fetal health. This essential guide provides healthcare practitioners, researchers, clinical experts, and students with insights into AI's practical uses and future potential, serving as a valuable reference for AI-driven diagnostic advancements and healthcare solutions.