Explainable Machine Learning Model for Predicting First-Time Acute Exacerbation in Patients with Chronic Obstructive Pulmonary Disease

Background: The study developed accurate explainable machine learning (ML) models for predicting first-time acute exacerbation of chronic obstructive pulmonary disease (COPD, AECOPD) at an individual level. Methods: We conducted a retrospective case–control study. A total of 606 patients with COPD w...

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Detalles Bibliográficos
Autores principales: Kor, Chew-Teng, Li, Yi-Rong, Lin, Pei-Ru, Lin, Sheng-Hao, Wang, Bing-Yen, Lin, Ching-Hsiung
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8879653/
https://www.ncbi.nlm.nih.gov/pubmed/35207716
http://dx.doi.org/10.3390/jpm12020228

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8879653/
https://www.ncbi.nlm.nih.gov/pubmed/35207716
http://dx.doi.org/10.3390/jpm12020228

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