Artificial Intelligence, Machine Learning, and Deep Learning in Precision Medicine in Liver Diseases - Concept, Technology, Application and Perspectives - 신간POD상품

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신간POD: 신간도서이나 출판사의 물류비 절감을 위해 주문시마다 제작하는 도서

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Editors: Tung-Hung Su, Jia-Horng Kao

ISBN: 9780323991360

Imprint: Academic Press

Published: August 20, 2023

Pages: 350

Paperback

Description

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.

Key features

• 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

Readership

Researchers focusing on AI in medicine and hepatologists, Bioinformaticians and/or data scientists with a focus on hepatology

Table of contents

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

About the editors

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.

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.