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AI-powered advances in pharmacology

IGI Global.

AI-powered advances in pharmacology

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	AI-powered advances in pharmacologyAminabee Shaik, editor.
其他題名:	Artificial intelligence-powered advances in pharmacology
其他作者:	Shaik, Aminabee,
出版者:	Hershey, Pennsylvania :IGI Global,2025.
面頁冊數:	1 online resource (xxiv, 488 p.) :ill. (some col.)
標題:	Artificial intelligence.
電子資源:	http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/979-8-3693-3212-2
ISBN:	9798369332139$q(ebook)

AI-powered advances in pharmacology
AI-powered advances in pharmacology[electronic resource] /Artificial intelligence-powered advances in pharmacologyAminabee Shaik, editor. - Hershey, Pennsylvania :IGI Global,2025. - 1 online resource (xxiv, 488 p.) :ill. (some col.) - Advances in medical technologies and clinical practice (AMTCP) book series. - Advances in medical technologies and clinical practice (AMTCP) book series..

Includes bibliographical references and index.

Foreword -- Preface -- Acknowledgment -- Chapter 1. Role of AI in Advancing Pharmacology -- Chapter 2. Advancing Telemedicine With Artificial Intelligence (AI): A Paradigm Shift in Pharmacology -- Chapter 3. Study on AI-Powered Advanced Drug Discovery for Enhancing Privacy and Innovation in Healthcare -- Chapter 4. AI in Predictive Toxicology -- Chapter 5. AI in Predictive Toxicology -- Chapter 6. Artificial Intelligence-Enhanced Nanomedicine Design and Deep Reinforcement Learning in Pharmacokinetics -- Chapter 7. Quantum Computing: A Catalyst for Drug Discovery Evolution -- Chapter 8. Blockchain for Pharmaceutical Data Management and Quantum Computing Innovations -- Chapter 9. Social Listening in Pharmacovigilance: Uncovering Unreported Adverse Drug Reactions With NLP -- Chapter 10. Heart Health Monitoring Using IoT and Machine Learning Methods -- Chapter 11. Identification and Targeting Growth Factor-Enhancing Transcripts in Aedes albopictus: A Therapeutic Approach -- Chapter 12. Future Trends and Challenges in Pharmaceutical Microbiology with the Integration of Artificial Intelligence -- Chapter 13. Business Practices in the Age of AI: The Role of AI Pharmacists in Drug Management -- Chapter 14. Transforming Hospitality, Personalized Medicine, and Adaptive Learning: Robotic Innovations -- Compilation of References -- About the Contributors -- Index.

"In the field of pharmaceutical sciences, the integration of artificial intelligence (AI) has emerged as a groundbreaking force, propelling the field into uncharted territories of discovery and innovation. As traditional approaches in drug discovery and development encounter new challenges, the need for cutting-edge technologies becomes increasingly apparent. AI-Powered Advances in Pharmacology offers an insightful exploration of this critical intersection between AI and pharmacological research. This book delves into how AI technologies are reshaping the understanding of diseases, predicting drug responses, and optimizing therapeutic interventions. It navigates through the relationship between AI algorithms, big data analytics, and traditional pharmacological methodologies, promising to accelerate drug development and usher in a new era of precision medicine. The primary objective of AI-Powered Advances in Pharmacology is to conduct a thorough exploration of the integration of artificial intelligence (AI) into pharmacological research, shedding light on its transformative impact on drug discovery, development, and personalized medicine. This comprehensive overview aims to serve as a valuable resource for researchers, practitioners, and students in the field, bridging the gap between traditional pharmacological approaches and AI methodologies. Through case studies and discussions of emerging trends, the book contributes to the evolving landscape of pharmacology, fostering a deeper understanding of diseases, optimizing therapeutic interventions, and shaping the future of precision medicine. By providing practical insights, it aims to inspire further advancements at the intersection of artificial intelligence and pharmacology."--

Mode of access: World Wide Web.

ISBN: 9798369332139$q(ebook)Subjects--Topical Terms:

194058
Artificial intelligence.
Subjects--Index Terms:

AI-Driven Drug Repurposing.Index Terms--Genre/Form:

214472
Electronic books.

LC Class. No.: RS122.2 / .A37 2024eb

Dewey Class. No.: 615.10285

National Library of Medicine Call No.: QV 26.5 / .A37 2024eb

AI-powered advances in pharmacology
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520 3 $a "In the field of pharmaceutical sciences, the integration of artificial intelligence (AI) has emerged as a groundbreaking force, propelling the field into uncharted territories of discovery and innovation. As traditional approaches in drug discovery and development encounter new challenges, the need for cutting-edge technologies becomes increasingly apparent. AI-Powered Advances in Pharmacology offers an insightful exploration of this critical intersection between AI and pharmacological research. This book delves into how AI technologies are reshaping the understanding of diseases, predicting drug responses, and optimizing therapeutic interventions. It navigates through the relationship between AI algorithms, big data analytics, and traditional pharmacological methodologies, promising to accelerate drug development and usher in a new era of precision medicine. The primary objective of AI-Powered Advances in Pharmacology is to conduct a thorough exploration of the integration of artificial intelligence (AI) into pharmacological research, shedding light on its transformative impact on drug discovery, development, and personalized medicine. This comprehensive overview aims to serve as a valuable resource for researchers, practitioners, and students in the field, bridging the gap between traditional pharmacological approaches and AI methodologies. Through case studies and discussions of emerging trends, the book contributes to the evolving landscape of pharmacology, fostering a deeper understanding of diseases, optimizing therapeutic interventions, and shaping the future of precision medicine. By providing practical insights, it aims to inspire further advancements at the intersection of artificial intelligence and pharmacology."-- $c Provided by publisher.
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653 $a Deep Reinforcement Learning in Pharmacokinetics.
653 $a Explainable AI in Pharmacology.
653 $a Genomic Data Integration for Precision Pharmacology.
653 $a Natural Language Processing in Literature Mining for Drug Discovery.
653 $a Neuropharmacology and Brain-Computer Interfaces.
653 $a Predictive Toxicology Applications of AI.
653 $a Quantum Computing Applications in Drug Discovery.
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