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Da: Kennys Bookshop and Art Galleries Ltd., Galway, GY, Irlanda
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Aggiungi al carrelloCondizione: New. 2022. 1st Edition. Hardback. . . . . .
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Aggiungi al carrelloGebunden. Condizione: New. Inamuddin, PhD, is an assistant professor at King Abdulaziz University, Jeddah, Saudi Arabia, and is also an assistant professor in the Department of Applied Chemistry, Aligarh Muslim University, Aligarh, India. He has extensive research experience in multi.
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Aggiungi al carrelloHardcover. Condizione: Brand New. 380 pages. 9.29x6.26x1.06 inches. In Stock.
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Aggiungi al carrelloCondizione: New. 2022. 1st Edition. Hardback. . . . . . Books ship from the US and Ireland.
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Aggiungi al carrelloBuch. Condizione: Neu. Neuware - DRUG DESIGN USING MACHINE LEARNINGThe use of machine learning algorithms in drug discovery has accelerated in recent years and this book provides an in-depth overview of the still-evolving field.The objective of this book is to bring together several chapters that function as an overview of the use of machine learning and artificial intelligence applied to drug development. The initial chapters discuss drug-target interactions through machine learning for improving drug delivery, healthcare, and medical systems. Further chapters also provide topics on drug repurposing through machine learning, drug designing, and ultimately discuss drug combinations prescribed for patients with multiple or complex ailments.This excellent overview\* Provides a broad synopsis of machine learning and artificial intelligence applications to the advancement of drugs;\* Details the use of molecular recognition for drug development through various mathematical models;\* Highlights classical as well as machine learning-based approaches to study target-drug interactions in the field of drug discovery;\* Explores computer-aided technics for prediction of drug effectiveness and toxicity.AudienceThe book will be useful for information technology professionals, pharmaceutical industry workers, engineers, university researchers, medical practitioners, and laboratory workers who have a keen interest in the area of machine learning and artificial intelligence approaches applied to drug advancements.
Da: Revaluation Books, Exeter, Regno Unito
EUR 260,16
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Aggiungi al carrelloHardcover. Condizione: Brand New. 380 pages. 9.29x6.26x1.06 inches. In Stock. This item is printed on demand.
Lingua: Inglese
Editore: John Wiley & Sons Inc, New York, 2022
ISBN 10: 1394166281 ISBN 13: 9781394166282
Da: CitiRetail, Stevenage, Regno Unito
EUR 240,63
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Aggiungi al carrelloHardcover. Condizione: new. Hardcover. DRUG DESIGN USING MACHINE LEARNING The use of machine learning algorithms in drug discovery has accelerated in recent years and this book provides an in-depth overview of the still-evolving field. The objective of this book is to bring together several chapters that function as an overview of the use of machine learning and artificial intelligence applied to drug development. The initial chapters discuss drug-target interactions through machine learning for improving drug delivery, healthcare, and medical systems. Further chapters also provide topics on drug repurposing through machine learning, drug designing, and ultimately discuss drug combinations prescribed for patients with multiple or complex ailments. This excellent overview Provides a broad synopsis of machine learning and artificial intelligence applications to the advancement of drugs;Details the use of molecular recognition for drug development through various mathematical models;Highlights classical as well as machine learning-based approaches to study target-drug interactions in the field of drug discovery;Explores computer-aided technics for prediction of drug effectiveness and toxicity. Audience The book will be useful for information technology professionals, pharmaceutical industry workers, engineers, university researchers, medical practitioners, and laboratory workers who have a keen interest in the area of machine learning and artificial intelligence approaches applied to drug advancements. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.