- 350 pages
- English
- PDF
- Available on iOS & Android
eBook - PDF
Artificial Intelligence in Urologic Malignancies
About this book
Artificial Intelligence in Urologic Malignancies describes current artificial intelligence technology, with an emphasis on prostate cancer applications. The book provides guidance on how artificial intelligence can improve therapeutics, how the power of artificial intelligence integrated with current standard therapy and research can enhance decision-making, and proposes future directions on how to integrate artificial intelligence within clinical applications. This is the perfect reference for scientists and researchers interested in the basic translational research opportunities such as drug discovery, pharmacogenetics, and experimental therapeutics, as well as clinicians interested in how AI applications are integrated with applications.
- Provides guidance on AI integration that is expected to become standard in the future
- Places a special emphasis on prostate cancer and the integration of AI to show how to enhance personalized medicine
- Surveys current techniques and standards that can be shared and applied to fields outside cancer
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Yes, you can access Artificial Intelligence in Urologic Malignancies by Himanshu Arora in PDF and/or ePUB format, as well as other popular books in Biological Sciences & Biology. We have over one million books available in our catalogue for you to explore.
Information
Table of contents
- Front Cover
- Artificial Intelligence in Urologic Malignancies
- Copyright Page
- Contents
- List of contributors
- Preface
- 1 Current advancements of machine learning in healthcare
- 2 Machine learning and pathology: a historical perspective
- 3 Artificial intelligence in personalized medicine: application of genomics to influence therapy decisions
- 4 Artificial intelligence in personalized medicine: Using public repositories to understand patterns in relevant datasets
- 5 Mutational landscape of cancer and how latest technologies can help in simplifying the understanding
- 6 ChatGPT and healthcareâcurrent and future prospects
- 7 Adversarial networksâenhancing current methodology with new models
- 8 Limitations of artificial intelligence in healthcare
- Index
- Back Cover