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 |
UN SDG
此研究成果有助於以下永續發展目標
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SDG 3 良好的健康和福祉
ASJC Scopus subject areas
- 一般生物化學,遺傳學和分子生物學
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