Utvidet returrett til 31. januar 2025

Machine Learning and AI in Clinical Practice

Om Machine Learning and AI in Clinical Practice

Machine Learning and AI in Clinical Practice: Revolutionizing Diagnosis and Treatment Strategies is a groundbreaking book that delves into the world of artificial intelligence (AI) and machine learning (ML) in healthcare. With advancements in technology, AI and ML have become integral parts of clinical practice, revolutionizing the way diagnoses are made and treatments are administered. This book provides a comprehensive overview of the latest AI and ML applications in healthcare, offering a glimpse into the future of medicine. From predicting treatment outcomes and identifying patient risk factors to drug discovery and personalized medicine, the potential applications of AI and ML in healthcare are limitless. The authors, a team of leading experts in the field, explore the benefits and challenges of using AI and ML in clinical practice, and provide valuable insights into the ethical and social considerations of this rapidly-evolving technology. They also discuss the potential impact on healthcare operations and the need for continued research and development to ensure the responsible use of AI and ML in medicine. Whether you are a healthcare professional, a researcher, or simply interested in the future of medicine, Machine Learning and AI in Clinical Practice is an essential guide to understanding the latest advancements in this exciting field. With detailed explanations of key concepts and real-world case studies, this book is both informative and accessible. Don't miss out on the opportunity to learn about the latest developments in AI and ML in healthcare. This book is a must-read for anyone interested in the future of medicine and the potential for technology to revolutionize clinical practice. Order your copy today and discover the endless possibilities of AI and ML in healthcare.

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  • Språk:
  • Engelsk
  • ISBN:
  • 9782231913557
  • Bindende:
  • Paperback
  • Sider:
  • 110
  • Utgitt:
  • 1. juni 2023
  • Dimensjoner:
  • 152x6x229 mm.
  • Vekt:
  • 173 g.
  • BLACK NOVEMBER
Leveringstid: 2-4 uker
Forventet levering: 19. desember 2024

Beskrivelse av Machine Learning and AI in Clinical Practice

Machine Learning and AI in Clinical Practice: Revolutionizing Diagnosis and Treatment Strategies is a groundbreaking book that delves into the world of artificial intelligence (AI) and machine learning (ML) in healthcare. With advancements in technology, AI and ML have become integral parts of clinical practice, revolutionizing the way diagnoses are made and treatments are administered.
This book provides a comprehensive overview of the latest AI and ML applications in healthcare, offering a glimpse into the future of medicine. From predicting treatment outcomes and identifying patient risk factors to drug discovery and personalized medicine, the potential applications of AI and ML in healthcare are limitless.
The authors, a team of leading experts in the field, explore the benefits and challenges of using AI and ML in clinical practice, and provide valuable insights into the ethical and social considerations of this rapidly-evolving technology. They also discuss the potential impact on healthcare operations and the need for continued research and development to ensure the responsible use of AI and ML in medicine.
Whether you are a healthcare professional, a researcher, or simply interested in the future of medicine, Machine Learning and AI in Clinical Practice is an essential guide to understanding the latest advancements in this exciting field. With detailed explanations of key concepts and real-world case studies, this book is both informative and accessible.
Don't miss out on the opportunity to learn about the latest developments in AI and ML in healthcare. This book is a must-read for anyone interested in the future of medicine and the potential for technology to revolutionize clinical practice. Order your copy today and discover the endless possibilities of AI and ML in healthcare.

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