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.
1. Artificial Intelligence in Urologic Malignancies - p. Page i 2. Cover - p. Page i 3. Title page - p. Page ii 4. Table of Contents - p. Page iii 5. Copyright - p. Page iii 6. Contents - p. Page vi 7. List of contributors - p. Page vii 8. Preface - p. Page vii 9. List of Illustrations - p. Page x 10. List of Tables - p. Page xi 11. Chapter 1 : Current advancements of machine learning in healthcare - p. Page xi 12. Chapter 2 : Machine learning and pathology: a historical perspective - p. Page 27 13. Chapter 3 : Artificial intelligence in personalized medicine: application of genomics to influence therapy decisions - p. Page 70 14. Chapter 4 : Artificial intelligence in personalized medicine: Using public repositories to understand patterns in relevant datasets - p. Page 105 15. Chapter 5 : Mutational landscape of cancer and how latest technologies can help in simplifying the understanding - p. Page 136 16. Chapter 6 : ChatGPT and healthcare—current and future prospects - p. Page 167 17. Chapter 7 : Adversarial networks—enhancing current methodology with new models - p. Page 192 18. Chapter 8 : Limitations of artificial intelligence in healthcare - p. Page 229 19. Index - p. Page 245
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.
1. Artificial Intelligence in Urologic Malignancies - p. Page i 2. Cover - p. Page i 3. Title page - p. Page ii 4. Table of Contents - p. Page iii 5. Copyright - p. Page iii 6. Contents - p. Page vi 7. List of contributors - p. Page vii 8. Preface - p. Page vii 9. List of Illustrations - p. Page x 10. List of Tables - p. Page xi 11. Chapter 1 : Current advancements of machine learning in healthcare - p. Page xi 12. Chapter 2 : Machine learning and pathology: a historical perspective - p. Page 27 13. Chapter 3 : Artificial intelligence in personalized medicine: application of genomics to influence therapy decisions - p. Page 70 14. Chapter 4 : Artificial intelligence in personalized medicine: Using public repositories to understand patterns in relevant datasets - p. Page 105 15. Chapter 5 : Mutational landscape of cancer and how latest technologies can help in simplifying the understanding - p. Page 136 16. Chapter 6 : ChatGPT and healthcare—current and future prospects - p. Page 167 17. Chapter 7 : Adversarial networks—enhancing current methodology with new models - p. Page 192 18. Chapter 8 : Limitations of artificial intelligence in healthcare - p. Page 229 19. Index - p. Page 245
