摘要

The development of artificial intelligence (AI) combined with the application of electronic health records (EHRs) has made precision medicine possible, tailoring liver disease prediction and treatment for various patient populations. Extended from precision medicine, the concepts of precision health and earlier medicine provide a wide-ranging scope to cover health promotion, disease prevention, and disease management. With the help of Taiwan's National Health Insurance claims databases, AI-based earlier medicine has realized liver disease prevention that is actionable, accurate, timely, and individualized. In this chapter, we provide two examples of EHRs used to predict fatty liver and liver cancer, introducing their data preprocessing, variable selection, machine learning model building, and model validation. Such predictive tools with promising performance enable high-risk patients to take preemptive actions. Moreover, from the perspective of a learning health care system, issues such as persistent data collection and integration, people's acceptance, and the availability of a system remain future challenges.
原文英語
主出版物標題Artificial Intelligence, Machine Learning, and Deep Learning in Precision Medicine in Liver Diseases
主出版物子標題Concept, Technology, Application and Perspectives
發行者Elsevier
頁面81-91
頁數11
ISBN(電子)9780323991360
ISBN(列印)9780323993760
DOIs
出版狀態已發佈 - 1月 1 2023

ASJC Scopus subject areas

  • 一般生物化學,遺傳學和分子生物學

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