Artificial Intelligence in Precision Drug Design: Advanced Applications showcases how artificial intelligence (AI) is revolutionizing modern drug discovery and development. Building upon the foundational principles established in Volume 1, this book dives into real-world applications where AI accelerates innovation, enhances predictive accuracy, and enables breakthrough therapeutics. Featuring contributions from leading global researchers and practitioners, the book explores machine learning, deep learning, and network-based approaches applied to complex biomedical challenges. Key areas include AI driven drug repurposing, combination therapies, immunotherapy, vaccine design, quantum computing, and the integration of large language models in drug discovery. Additional chapters highlight predictive modeling using electronic health records, AI-powered medical imaging, and explainable AI for structure-based drug design. What sets this volume apart is its emphasis on practical impact, demonstrating how data, computation, and interdisciplinary collaboration converge to advance precision medicine. Designed for scientists, clinicians, educators, and students, it serves as both a comprehensive reference and a source of inspiration for leveraging AI to transform healthcare.
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Dr. Khalid Raza is an Associate Professor at the Department of Computer Science, Jamia Millia Islamia, New Delhi, India, and an Adjunct Professor at UCSI University, Malaysia. He has over 14 years of teaching and research experience and previously served as an ICCR Chair Visiting Professor at Ain Shams University, Egypt. Dr. Raza has published more than 160 peer-reviewed papers and authored/edited over 15 books with Springer, Elsevier, and CRC Press. He serves as Academic Editor of PLoS ONE, BMC Artificial Intelligence, and Guest Editor of npj Precision Oncology, JoVE, and several other journals. Recipient of Clarivate’s (Web of Science) India Excellence Research Citation Award 2025, Dr. Raza is consistently featured in the World’s Top 2% Scientists list (2022–2025). His research focuses on AI, bioinformatics, and health informatics
Artificial Intelligence in Precision Drug Design: Advanced Applications showcases how artificial intelligence (AI) is revolutionizing modern drug discovery and development. Building upon the foundational principles established in Volume 1, this book dives into real-world applications where AI accelerates innovation, enhances predictive accuracy, and enables breakthrough therapeutics. Featuring contributions from leading global researchers and practitioners, the book explores machine learning, deep learning, and network-based approaches applied to complex biomedical challenges. Key areas include AI driven drug repurposing, combination therapies, immunotherapy, vaccine design, quantum computing, and the integration of large language models in drug discovery. Additional chapters highlight predictive modeling using electronic health records, AI-powered medical imaging, and explainable AI for structure-based drug design. What sets this volume apart is its emphasis on practical impact, demonstrating how data, computation, and interdisciplinary collaboration converge to advance precision medicine. Designed for scientists, clinicians, educators, and students, it serves as both a comprehensive reference and a source of inspiration for leveraging AI to transform healthcare.
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Zustand: New. - Focuses on real-world AI applications in drug design and development provides comprehensive coverage of advanced techniques: deep learning, network-based models, and quantum computing.- Includes case studies on drug repurposing, combination therapies,. Artikel-Nr. 2769883150
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Taschenbuch. Zustand: Neu. Neuware - Artificial Intelligence in Precision Drug Design, Volume One: Foundations and Core Techniques offers a comprehensive introduction to the transformative role of AI in modern drug discovery. The book lays the groundwork for understanding how machine learning, deep learning, and generative models are reshaping the development of precision therapeutics. It explores foundational topics such as AI-driven molecular screening, pharmacokinetics, ADMET modeling, toxicity prediction, and omics integration. In addition, sections address ethical, philosophical, and epistemological dimensions, ensuring a well-rounded perspective. Each chapter, authored by global experts, combines theoretical insights with real-world case studies to bridge the gap between AI and life sciences.Designed for graduate students, researchers, and professionals in bioinformatics, biomedical sciences, and pharmaceutical R&D, this volume equips readers with essential knowledge and tools to navigate the evolving landscape of AI in drug design. It empowers interdisciplinary learners to apply cutting-edge AI techniques to real-world biomedical challenges. Artikel-Nr. 9780443444159
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