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  4. Machine Learning Models for ASCVD Risk Prediction in an Asian Population - How to Validate the Model is Important
 
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Machine Learning Models for ASCVD Risk Prediction in an Asian Population - How to Validate the Model is Important

Journal
Acta Cardiologica Sinica
Journal Volume
39
Journal Issue
6
Pages
901
Date Issued
2023-11
Author(s)
Hsiao, Yu-Chung
Kuo, Chen-Yuan
FANG-JU LIN  
YEN-WEN WU  
Lin, Tsung-Hsien
Yeh, Hung-I
Chen, Jaw-Wen
CHAU-CHUNG WU  
DOI
10.6515/ACS.202311_39(6).20230528A
URI
https://scholars.lib.ntu.edu.tw/handle/123456789/640826
URL
https://api.elsevier.com/content/abstract/scopus_id/85182699860
Abstract
Atherosclerotic cardiovascular disease (ASCVD) is prevalent worldwide including Taiwan, however widely accepted tools to assess the risk of ASCVD are lacking in Taiwan. Machine learning models are potentially useful for risk evaluation. In this study we used two cohorts to test the feasibility of machine learning with transfer learning for developing an ASCVD risk prediction model in Taiwan.
Subjects
Atherosclerotic cardiovascular disease; Machine learning; Risk prediction model
Publisher
TAIWAN SOC CARDIOLOGY
Type
journal article

臺大位居世界頂尖大學之列,為永久珍藏及向國際展現本校豐碩的研究成果及學術能量,圖書館整合機構典藏(NTUR)與學術庫(AH)不同功能平台,成為臺大學術典藏NTU scholars。期能整合研究能量、促進交流合作、保存學術產出、推廣研究成果。

To permanently archive and promote researcher profiles and scholarly works, Library integrates the services of “NTU Repository” with “Academic Hub” to form NTU Scholars.

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開放取用是從使用者角度提升資訊取用性的社會運動,應用在學術研究上是透過將研究著作公開供使用者自由取閱,以促進學術傳播及因應期刊訂購費用逐年攀升。同時可加速研究發展、提升研究影響力,NTU Scholars即為本校的開放取用典藏(OA Archive)平台。(點選深入了解OA)

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