Deep Learning for Targeted Treatments: Transformation in Healthcare

The book "Deep Learning for Targeted Treatments" highlights the importance of deep learning in various areas of healthcare, including targeted treatment, biological systems, drug delivery, and risk assessment. It emphasizes the use of deep learning in patient care, disease imaging, and health management, with a focus on leveraging its potential for targeted therapy of diseases. The book is intended for researchers, professionals, and students in clinical research, disease management, pharmaceuticals, R&D, deep learning analytics, remote healthcare management, healthcare analytics, and deep learning in the healthcare industry.

Format: Hardback
Length: 464 pages
Publication date: 28 September 2022
Publisher: John Wiley & Sons Inc

The book provides a comprehensive guide for future research in deep learning, emphasizing its significant role in targeted treatment, biological systems, site-specific drug delivery, risk assessment in therapy, and other areas. It explores the importance of deep learning in patient care, disease imaging/detection, and health management. By leveraging the capabilities of deep learning to control drug delivery to targeted tissues or organs, the book aims to explore the potential of the DL framework for targeted therapy of various diseases.

In terms of its industrial significance, deep learning is widely implemented in pharmaceutical healthcare. The book is designed to appeal to a wide audience, including researchers, professionals working in clinical research, disease management, pharmaceuticals, R&D formulation, deep learning analytics, remote healthcare management, healthcare analytics, and deep learning in the healthcare industry.

The book is organized into five chapters, each covering different aspects of deep learning for targeted treatments. Chapter 1 provides an introduction to deep learning and its applications in healthcare. Chapter 2 discusses the role of deep learning in targeted treatment, including drug discovery, personalized medicine, and cancer therapy. Chapter 3 explores the use of deep learning in biological systems, such as gene expression analysis and protein structure prediction. Chapter 4 discusses site-specific drug delivery, including drug targeting and nanotechnology. Chapter 5 discusses risk assessment in therapy, including machine learning algorithms and clinical decision support systems.

Throughout the book, real-world examples and case studies are used to illustrate the practical applications of deep learning in healthcare. The authors have drawn on their extensive experience and expertise in the field to provide a comprehensive and up-to-date overview of the latest developments in deep learning for targeted treatments.

In conclusion, the book "Deep Learning for Targeted Treatments" is a valuable resource for researchers, professionals, and students interested in advancing the field of deep learning in healthcare. It provides a comprehensive guide for future research and practical applications, highlighting the significant role of deep learning in targeted treatment, biological systems, site-specific drug delivery, risk assessment in therapy, and other areas. With its wide audience and up-to-date coverage, the book is sure to become a staple in the field of deep learning in healthcare.

Weight: 930g
ISBN-13: 9781119857327