Machine learning approaches for practical predicting outpatient near-future AECOPD based on nationwide electronic medical records.
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ABSTRACT:
SUBMITTER: Liao KM
PROVIDER: S-EPMC10993192 | biostudies-literature | 2024 Apr
REPOSITORIES: biostudies-literature
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Machine learning approaches for practical predicting outpatient near-future AECOPD based on nationwide electronic medical records.
Liao Kuang-Ming KM Cheng Kuo-Chen KC Sung Mei-I MI Shen Yu-Ting YT Chiu Chong-Chi CC Liu Chung-Feng CF Ko Shian-Chin SC
iScience 20240320 4
In this research, we aimed to harness machine learning to predict the imminent risk of acute exacerbation in chronic obstructive pulmonary disease (AECOPD) patients. Utilizing retrospective data from electronic medical records of two Taiwanese hospitals, we identified 26 critical features. To predict 3- and 6-month AECOPD occurrences, we deployed five distinct machine learning algorithms alongside ensemble learning. The 3-month risk prediction was best realized by the XGBoost model, achieving an ...[more]
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