Abstract

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.

Original languageEnglish
Title of host publicationArtificial Intelligence, Machine Learning, and Deep Learning in Precision Medicine in Liver Diseases
Subtitle of host publicationConcept, Technology, Application and Perspectives
PublisherElsevier
Pages81-91
Number of pages11
ISBN (Electronic)9780323991360
ISBN (Print)9780323993760
DOIs
Publication statusPublished - Jan 1 2023

Keywords

  • Artificial intelligence
  • Earlier medicine
  • Electronic health record
  • Precision health
  • Prediction of liver disease

ASJC Scopus subject areas

  • General Biochemistry,Genetics and Molecular Biology

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