Shivam Rajput

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.

This book explores the transformative role of artificial intelligence (AI) in diagnosing and treating neurological disorders. It offers a comprehensive overview of how AI can enhance diagnostic accuracy, improve treatment plans, and ultimately lead to better patient outcomes in the realm of neural health. It covers a wide range of topics, including fundamental AI technologies and their relevance in neural health, detailed case studies demonstrating the application of AI in diagnosing and treating neurological conditions, and the ethical, legal, and social implications of using AI in healthcare. It also delves into future trends and innovations in AI-driven neural health solutions. The book is essential for healthcare professionals, AI researchers, and neuroscientists as it bridges the gap between cutting-edge AI technologies and practical medical applications.

This book offers a comprehensive exploration of the convergence of generative artificial intelligence and disability assistance, seeking to highlight the revolutionary capabilities of AI technology in improving the lives of those with disabilities. Given the swift progression of AI capabilities, it is vital to comprehend how these innovations might be used to foster inclusivity, enhance accessibility, and deliver personalised assistance. This book aims to connect advanced research and practical applications with the specific requirements of individuals with disabilities. The book offers a detailed investigation of generative AI as an assistive tool for individuals with disabilities, encompassing fundamental principles of generative AI, case studies of effective applications, and critical analyses of ethical considerations and societal implications. The book provides a comprehensive analysis of several applications of generative AI for individuals with disabilities across various domains. Examples of generative AI applications encompass AI-assisted communication tools for individuals with speech problems, customised educational platforms for students with learning challenges, virtual reality settings that improve social engagement for individuals on the autistic spectrum and various others. These applications demonstrate how generative AI may improve accessibility and empower individuals by personalising experiences to their individual requirements.

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.

“A ground-breaking compilation that focuses on the integration of artificial intelligence and machine learning applications in cardiovascular healthcare... Offers helpful insights into the enormous potential of AI to change the landscape of cardiovascular care, from basic AI concepts to the most recent developments in AI-assisted wearables and diagnostic imaging.”—From the Foreword by Dr. Dhruv Galgotia, CEO–Galgotias University, IndiaToday, the need for effective and cutting-edge methods of diagnosis, treatment, and prevention of cardiovascular diseases is greater than ever before. Integrating deep learning and artificial intelligence into digital healthcare and medical environments has the potential to revolutionize cardiovascular health. The new book addresses this need by discussing emerging uses of artificial intelligence and machine learning in the prediction, diagnosis, treatment, and management of cardiovascular diseases. It looks at AI in wearable technology, nuclear cardiac imaging, coronary CT angiography, and non-contrast cardiac CT methods. It also explores the application of machine learning techniques in predicting and diagnosing cardiovascular diseases, revealing the potential for data-driven predictions and decisions that can improve patient outcomes. It explores the potential of AI in a variety of cardiology applications, including the classification of ECG signals, wearables with AI support, speech technologies in clinical settings, and more.

ARTIFICIAL INTELLIGENCE FOR BONE DISORDER The authors have produced an invaluable resource that connects the fields of AI and bone treatment by providing essential insights into the current state and future of AI in bone condition diagnosis and therapy, as well as a methodical examination of machine learning algorithms, deep learning approaches, and their real-world uses. The book explores the use of artificial intelligence (AI) in the diagnosis and treatment of various bone illnesses. The integration of AI approaches in the fields of orthopedics, radiography, tissue engineering, and other areas related to bone are discussed in detail. It covers tissue engineering methods for bone regeneration and investigates the use of AI tools in this area, emphasizing the value of deep learning and how to use AI in tissue engineering efficiently. The book also covers diagnostic and prognostic uses of AI in orthopedics, such as the diagnosis of disorders involving the hip and knee as well as prognoses for therapies. Chapters also look at MRI, trabecular biomechanical strength, and other methods for diagnosing osteoporosis. Other issues the book examines include several uses of AI in pediatric orthopedics, 3D modeling, digital X-ray radiogrammetry, convolutional neural networks for customized care, and digital tomography. With information on the most recent developments and potential future applications, each chapter of the book advances our understanding of how AI might be used to diagnose and treat bone problems. Audience This book will serve as a guide for orthopedic experts, biomedical engineers, faculty members, research scholars, IT specialists, healthcare workers, and hospital administrators.