| ISBN13: | 9780323991360 |
| ISBN10: | 032399136X |
| Binding: | Paperback |
| No. of pages: | 350 pages |
| Size: | 235x191 mm |
| Weight: | 730 g |
| Language: | English |
| 631 |
Artificial Intelligence, Machine Learning, and Deep Learning in Precision Medicine in Liver Diseases
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Artificial Intelligence, Machine Learning, and Deep Learning in Precision Medicine and Liver Diseases: Concept, Technology, Application, and Perspectives combines four major applications of artificial intelligence (AI) within the field of clinical medicine specific to liver diseases: radiology imaging, electronic health records, pathology, and multiomics. The book provides a state-of-the-art summary of AI in precision medicine in hepatology, clarifying the concept and technology of AI and pointing to the current and future applications of AI within the field of hepatology. Coverage includes data preparation, methodology and application within disease-specific cases in fibrosis, viral and steatohepatitis, cirrhosis, hepatocellular carcinoma, acute liver failure, liver transplantation, and more. The ethical and legal issues of AI and future challenges and perspectives are also discussed.
By highlighting many new AI applications which can further research, diagnosis, and treatment, this reference is the perfect resource for both practicing hepatologists and researchers focused on AI applications in medicine.
- Introduces the concept of AI and machine learning of precision medicine in the field of hepatology
- Discusses current challenges of AI in healthcare and proposes future tasks for AI in new workflows of healthcare
- Provides real-world applications from domain experts in clinical medicine
Section 1. Basics of artificial intelligence in medicine 1. Artificial intelligence in healthcare: past and present 2. Data-centric artificial intelligence in health care: progress, shortcomings, and remedies
Section 2. Fields of AI in hepatology (by tools) data preparation methodology application 3. Artificial intelligence in radiology and application in liver disease 4. Electronic health record for artificial intelligence health care, and application to liver disease 5. Artificial intelligence in pathology and application to liver disease 6. Artificial intelligence using multiomics/genetic tools and application in liver disease
Section 3. AI application in specific tasks of liver diseases (by disease/tasks) 7. Artificial intelligence in prediction of steatosis and fibrosis of nonalcoholic fatty liver disease 8. Artificial intelligence in the prediction of progression and outcome in viral hepatitis 9. Artificial intelligence in cirrhosis complications and acute liver failure 10. Artificial intelligence in liver transplantation 11. Artificial intelligence in liver cancer: diagnosis and management 12. Predicting drug-induced liver injury with artificial intelligenceda minireview 13. Artificial intelligence in precision medicine and liver disease monitoring
Section 4. Perspectives of AI in liver diseases and beyond 14. Regulatory, social, ethical, and legal issues of artificial intelligence in medicine 15. Opportunities and challenges of explainable artificial intelligence in medicine: toward causability for physicians, developers, and patients 16. Outlook of future landscape of artificial intelligence in health care of liver disease and challenges
