Ensuring Reliable Generative AI in Healthcare: Challenges and Solutions for Diagnosis and Treatment Systems

This book provides a deep dive into how Generative Artificial Intelligence is fostering innovation apart from being impactful, and key problems that affect the healthcare ecosystem as a whole are now being solved. With the rapid rise of Generative Artificial Intelligence (AI), industries are changing rapidly, and healthcare is no exception. Generative AI, as a transformative subset of AI, has the extraordinary ability to create new data, simulate scenarios, and optimize complex processes. Its potential for medical diagnostics and drug development is beyond doubt and it is born to revolutionize medical research and Personalized treatment. Reasoning subtitled Generative AI for Healthcare, this exploratory volume on cutting-edge technology's profound impact on modern medicine is based on years of dedicated research.

Key highlights include:

· Using Generative AI to actually produce synthetic teaching sets and consequently re-armed medical-solving equipment will in turn enhance diagnosis and accuracy

· Reducing the amount of time and costs for developing drugs by means of artificial intelligence, by iterating through virtual compounds and simulating molecular environments

· Creating personalized treatment strategies out of specific patient profiles that embrace precision medicine, improving outcomes

· Simulating medical scenarios to measure the effectiveness of a cure in advance expensive, high-risk trials, the profound secrets behind complex diseases are slowly coming to light.

This book is designed to help the next generation of healthcare practices address research gaps, regulatory challenges, ethical considerations, and other concerns. Balancing rich case studies with practical insights and forward -looking ideas, this book aims to link up the promise of technological innovation in healthcare with its real application. The book also highlights the need for responsible AI adoption, addressing issues such as data privacy, bias reduction in models, explainable and reliable AI systems. The goal is to provide healthcare professionals, researchers and policy makers with knowledge and tools needed to use Generative AI responsibly and effectively. Whether you are a healthcare provider, AI researcher or industry innovator, Generative AI for Healthcare gives you an essential primer on how AI can be applied to transform patient care outcomes, drive medical research forward -- and even shape the future of healthcare itself.

Leverages next generation Generative AI applications Discusses the moral implications of AI Forecasts future trend

Autorentext

Dr. Mangesh M. Ghonge is a founder of MG Aricent Educational Foundation, Yavatmal, India. He received his Ph.D. in Computer Science & Engineering from Sant Gadge Baba Amravati University, Amravati, India. He authored/co-authored more than 100+ published articles in prestigious journals, books, and conferences. Besides, Dr. Mangesh Ghonge authored/edited more than 20 international books published by recognized publishers such as Elsevier, Springer, IGI Global, CRC Press Taylor & Francis, Wiley-Scrivener, Nova, De Gruyter, Bentham Science. More than 1300 Google citations to his credit. He has been invited as a resource person for many workshops/FDP. He has organized and chaired many national/international conferences and conducted various workshops. He is a registered Ph.D. supervisor with SPPU, Pune. He is also a guest editor for SCIE/Scopus-indexed journal special issues. His 04-patent published and 08 copyright granted. Dr. Mangesh Ghonge has 15 years of academic & industry experience and guided many research scholars.

Inhalt

Introduction to GenAI in Healthcare.- Revolutionizing Medical Imaging with Generative AI.- Role of Generative Artificial Intelligence in the Diagnosis, Treatment, and Prognosis of Head and Neck Cancer.- Generative AI for Drug Development and Clinical Trials.- eFBNet 1.0: An Automated Deep Network Model for Early Detection of Lung Cancer Utilizing Histopathological Image Classification.- Generative AI for Radiology: Innovations, Challenges, and Applications.- Through the Lens of AI: Investigating Retinoblastoma Diagnosis via Preprocessing and Explainable Transfer Learning.- AI-Driven Hybrid IoT System for Non-Invasive Diabetes Prediction Using Multi-Parametric Biosensor Fusion in Edge Wearables.- AI-Driven Innovation in Healthcare Applications.- AI Driven Innovations in Healthcare Applications Eye Gazing Technology for Detection of Neurological Disorders.- Integrating Generative AI into Healthcare: Current Innovations and Future Directions.- The Road Map Ahead: Integrating GenAI into Healthcare.