Artificial Intelligence, Machine Learning, and Deep Learning in Precision Medicine in Liver Diseases
Concept, Technology, Application and Perspectives
- 1st Edition - August 20, 2023
- Editors: Tung-Hung Su, Jia-Horng Kao
- Language: English
- Paperback ISBN:9 7 8 - 0 - 3 2 3 - 9 9 1 3 6 - 0
- eBook ISBN:9 7 8 - 0 - 3 2 3 - 9 9 3 7 6 - 0
Artificial Intelligence, Machine Learning, and Deep Learning in Precision Medicine and Liver Diseases: Concept, Technology, Application, and Perspectives combines four major app… Read more
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Request a sales quoteArtificial 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
Researchers focusing on AI in medicine and hepatologists, Bioinformaticians and/or data scientists with a focus on hepatology
- Cover image
- Title page
- Table of Contents
- Copyright
- List of contributors
- Section 1. Basics of artificial intelligence in medicine
- Chapter 1. Artificial intelligence in health care: past and present
- Chapter outlines
- Clinical applications
- Introduction
- Past: a brief history of artificial intelligence in health care
- Present: artificial intelligence in health care today
- Future: opportunities and challenges of artificial intelligence in health care
- Conclusion
- Chapter 2. Data-centric artificial intelligence in health care: progress, shortcomings, and remedies
- Introduction
- Training data generation and aggregation
- Fusing knowledge with generative adversarial networks
- Concluding remarks
- Section 2. Fields of artificial intelligence in hepatology, by tools, data preparation, methodology and application
- Chapter 3. Artificial intelligence in radiology and its application in liver disease
- Chapter outlines
- Clinical applications
- Introduction
- Radiomics
- Deep learning
- Conclusion
- Chapter 4. Electronic health record for artificial intelligence health care, and application to liver disease
- Chapter outlines
- Clinical applications
- Introduction
- Electronic health records in precision health
- Electronic health records applied to prediction of fatty liver
- Time series data used to predict liver cancer risk
- Conclusion
- Chapter 5. Artificial intelligence in pathology and application to liver disease
- Chapter outlines
- Clinical applications
- Introduction
- Role of pathology in liver disease diagnosis and staging
- Digital revolution of pathology
- Principles of artificial intelligence processing of whole-slide images
- Applications of artificial intelligence–based pathology
- Challenges to implementing artificial intelligence in pathology
- Conclusion
- Chapter 6. Artificial intelligence using multiomics/genetic tools and application in liver disease
- Introduction
- Multiomics data and their integration in hepatocellular carcinoma
- Conclusion
- Clinical applications
- Section 3. Artificial intelligence application in specific diseases of liver
- Chapter 7. Artificial intelligence in prediction of steatosis and fibrosis of nonalcoholic fatty liver disease
- Chapter outlines
- Clinical applications
- Introduction
- Current methods for assessing steatosis
- Artificial intelligence for predicting steatosis
- Current methods for assessing liver fibrosis
- Artificial intelligence for assessing histologic fibrosis
- Conclusions and the future
- Chapter 8. Artificial intelligence in the prediction of progression and outcomes in viral hepatitis
- Chapter outlines
- Clinical applications
- A brief introduction to artificial intelligence
- Artificial intelligence in the detection or prediction of liver fibrosis in chronic viral hepatitis
- Artificial intelligence in predicting gastroesophageal varices using computed tomography images
- Artificial intelligence in the diagnosis, prediction, and prognosis of hepatocellular carcinoma
- Future perspectives and limitations of artificial intelligence technology
- Conclusion
- Chapter 9. Artificial intelligence in cirrhosis complications and acute liver failure
- Chapter outlines
- Definition of terms
- Clinical applications
- Introduction
- Portal hypertension
- Gastroesophageal varices
- Ascites
- Hepatic encephalopathy
- Hepatorenal syndrome
- Portal vein thrombosis
- Transplantation and hepatocellular carcinoma
- Acute-on-chronic liver failure
- Acute liver failure
- Challenges
- Chapter 10. Artificial intelligence in liver transplantation
- Chapter outline
- Clinical applications
- Introduction
- Pretransplant
- Posttransplant
- Future directions
- Conclusion
- Chapter 11. Artificial intelligence in liver cancer: diagnosis and management
- Chapter outlines
- Clinical applications
- Introduction
- Overview of main machine learning models used in field of hepatocellular carcinoma
- Artificial intelligence–based differential diagnosis of hepatocellular carcinoma
- Artificial intelligence–based prediction of treatment response of hepatocellular carcinoma
- Artificial intelligence–based prediction of prognosis of hepatocellular carcinoma
- Conclusion
- Chapter 12. Predicting drug-induced liver injury with artificial intelligence—a minireview
- Disclaimer
- Chapter outlines
- Clinical applications
- What is drug-induced liver injury?
- Why drug-induced liver injury is important to drug development and public health
- Nonanimal approaches developed for drug-induced liver injury assessment
- How the drug-induced liver injury risk of a drug is determined
- Overview of computational methods for drug-induced liver injury prediction
- Discussion
- Conclusion
- Author contributions
- Conflict of interest
- Chapter 13. Artificial intelligence in precision medicine and liver disease monitoring
- Chapter outlines
- Clinical applications
- Precision medicine
- Artificial intelligence in monitoring liver disease
- Challenges and perspectives
- Section 4. Perspectives of AI in liver diseases and beyond
- Chapter 14. Regulatory, social, ethical, and legal issues of artificial intelligence in medicine
- Chapter outlines
- Clinical applications
- Introduction
- Gender bias
- Ethnic bias
- Taking control
- General principles of ethically aligned design
- Ethical guidelines for trustworthy artificial intelligence
- World Medical Association statement on augmented intelligence in medical care
- Conclusion
- Chapter 15. Opportunities and challenges of explainable artificial intelligence in medicine: toward causability for physicians, developers, and patients
- Clinical applications
- Introduction
- Explainable artificial intelligence in medicine
- Potential clinical applications and research directions of explainable artificial intelligence
- Explainable federated learning
- Limitations and trends in medical artificial intelligence
- Chapter 16. Outlook of future landscape of artificial intelligence in health care of liver disease and challenges
- Chapter outlines
- Clinical applications
- Introduction
- Short summary of artificial intelligence in liver disease
- Applications of artificial intelligence in medical care of liver disease patients in 2025
- Ongoing issues and challenges
- Perspectives
- Index
- No. of pages: 350
- Language: English
- Edition: 1
- Published: August 20, 2023
- Imprint: Academic Press
- Paperback ISBN: 9780323991360
- eBook ISBN: 9780323993760
TS
Tung-Hung Su
Dr. Tung-Hung Su is an experienced physician in hepatology and clinical Associate Professor of the National Taiwan University Hospital. He is actively carrying out research of AI application in liver diseases, using imaging, electronical health records, and pathology. He had published several papers using healthcare database for the outcome prediction in liver diseases and a review paper regarding AI in precision medicine in hepatology with Professor Jia-Horng Kao.
Affiliations and expertise
Medical Doctor, Division of Gastroenterology, National Taiwan University Hospital, Taipei, TaiwanJK
Jia-Horng Kao
Professor Jia-Horng Kao is an expert in liver diseases, past-president of the Taiwan Association for the Study of the Liver, and Chair Professor of the National Taiwan University. He has published more than 650 scientific papers and edited several books regarding viral hepatitis.
Affiliations and expertise
Chair Professor, National Taiwan University; Vice Superintendant, National Taiwan University Hospital, Taipei, TaiwanRead Artificial Intelligence, Machine Learning, and Deep Learning in Precision Medicine in Liver Diseases on ScienceDirect