Author : Anand Vemula
Publisher : Independently Published
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.3/5 (282 download)
Book Synopsis Generative AI in Drug Safety and Pharmacovigilance by : Anand Vemula
Download or read book Generative AI in Drug Safety and Pharmacovigilance written by Anand Vemula and published by Independently Published. This book was released on 2024-06-12 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Generative AI in Drug Safety and Pharmacovigilance: A Comprehensive Guide" is a groundbreaking exploration into the integration of generative artificial intelligence (AI) within the realm of drug safety and pharmacovigilance. Authored by leading experts in the field, this book offers a thorough examination of the potential applications, ethical considerations, regulatory compliance, and future trends of employing generative AI technologies. The book begins with an insightful introduction to the foundational principles of generative AI, elucidating its significance in revolutionizing drug safety and pharmacovigilance practices. Readers are guided through the historical evolution of generative AI models, from basic concepts to advanced algorithms such as Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and Transformers. Subsequently, the text delves into real-world applications of generative AI in pharmacovigilance, including adverse event detection, predictive analytics, data augmentation, and natural language processing (NLP). Through captivating case studies and practical examples, readers gain a comprehensive understanding of how generative AI can enhance drug safety monitoring systems and facilitate early detection of adverse drug reactions. Ethical and regulatory considerations take center stage in the following chapters, as the authors navigate complex issues surrounding data privacy, security, and the ethical use of AI in healthcare. Readers are provided with invaluable insights into compliance with international standards and guidelines, ensuring adherence to regulatory frameworks set forth by governing bodies. As the book concludes, it offers a glimpse into the future of generative AI in drug safety and pharmacovigilance, exploring emerging technologies and innovative approaches poised to shape the landscape of healthcare. With a forward-thinking perspective, the authors anticipate advancements in explainable AI, blockchain integration, and wearable technology, paving the way for enhanced patient safety and personalized medicine. "Generative AI in Drug Safety and Pharmacovigilance: A Comprehensive Guide" serves as an indispensable resource for healthcare professionals, researchers, and policymakers seeking to harness the power of generative AI to safeguard public health and revolutionize the pharmaceutical industry. Through its lucid explanations, practical insights, and visionary outlook, the book empowers readers to navigate the intersection of artificial intelligence and healthcare with confidence and foresight.