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Deep Learning for Targeted Treatments, authored by Rishabha Malviya, is a pivotal book that outlines the future of deep learning in healthcare. It emphasizes the importance of the deep learning framework in patient care, disease imaging, and health management. The book delves into the role of deep learning in targeted therapy for various diseases, making it a significant read for researchers and professionals in the healthcare industry.
Deep learning, a subset of machine learning, has the potential to revolutionize healthcare by providing insights that were previously inaccessible. It can help in disease prediction, patient care management, and drug delivery. The book explores the various prospects of deep learning in targeted therapy, making it an essential read for those interested in the application of AI in healthcare.
Targeted therapy is a treatment approach that focuses on specific molecules involved in the growth, progression, and spread of cancer cells. Deep learning can significantly enhance targeted therapy by identifying the most effective treatment strategies and predicting patient outcomes. The book provides a detailed analysis of how deep learning can improve targeted treatments, making it a valuable resource for researchers and healthcare professionals.
The implementation of deep learning in healthcare has significant industrial implications. It can improve drug delivery, streamline clinical trials, and enhance patient care. The book discusses the various ways in which deep learning is being used in the pharmaceutical industry, making it a must-read for professionals working in R&D, formulation, and healthcare analytics.
Deep Learning for Targeted Treatments is an invaluable resource for researchers, professionals, and students working in the areas of clinical research, disease management, pharmaceuticals, R&D formulation, deep learning analytics, remote healthcare management, and healthcare analytics. Published by Wiley in September 2022, the book is available in English and can be accessed through various online platforms.
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