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Generative AI in Healthcare: A Comprehensive Guide

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Book Details
Language
English
Publishers
Independently published (21 Jun. 2024)
Weight
0.15 KG
Publication Date
21/06/2024
Pages
104 pages
ISBN-13
9798329053036
Dimensions
15.24 x 0.61 x 22.86 cm
SKU
9798329053036
Author Name
Anand Vemula (Author)
Anand Vemula is a technology, business, ESG and Risk governance Evangelist. He has more than 27 plus years of experience. Has worked in MNC at a CXO level. Has been a part of various projects and forums across customers in BFSI, Healthcare, Retail, Manufacuring, Lifesciences, Energy Industry Verticals. Certified in all the technologies and Enterprise Digital ArchitectRead more about this authorRead less about this author
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Generative AI in Healthcare: A Comprehensive Guide" explores the transformative role of artificial intelligence (AI) in revolutionizing healthcare practices. This book serves as a comprehensive resource for healthcare professionals, technologists, and enthusiasts interested in understanding how generative AI is reshaping the future of medicine.

The book begins with an exploration of the foundational concepts of generative AI, providing insights into neural networks, deep learning fundamentals, and various generative models such as Variational Autoencoders (VAEs), Generative Adversarial Networks (GANs), and Transformer models. It delves into the importance of high-quality data and robust infrastructure necessary to support AI applications in healthcare settings.

Part II of the book focuses on practical applications of generative AI in healthcare, including enhancing medical imaging accuracy, accelerating drug discovery processes, and personalizing treatment plans based on individual patient data. Real-world case studies and examples illustrate how AI is automating tasks, improving diagnostic accuracy, and supporting clinical decision-making.

In Part III, the book addresses implementation challenges such as technical integration into existing healthcare systems, change management strategies, and ethical considerations around data privacy and algorithmic bias. It emphasizes the importance of training healthcare professionals to effectively leverage AI tools while adhering to regulatory standards.

Part IV explores future directions of generative AI in healthcare, discussing emerging technologies like AI-enabled IoT devices, quantum computing applications, and advanced AI models. Global perspectives highlight international collaborations and case studies from different countries, showcasing diverse approaches to integrating AI in healthcare.

Concluding with a forward-looking perspective, the book discusses long-term predictions for AI's role in healthcare, emphasizing its potential to enhance preventive care, improve patient outcomes, and streamline healthcare delivery. .

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