Advanced machine learning models for prediction of readmission and mortality risks in patients with chronic obstructive pulmonary disease using routine clinical data.
A machine learning approach based on clinical data readily available from the EHR performed better than existing models in predicting 30-day readmission and mortality risks in patients with COPD. A comprehensive risk prediction tool may enhance individualized care strategies and improve patient outcomes in COPD management.
Authors
- Ren Nishimoto
- Masashi Kondo (ORCID: https://orcid.org/0000-0001-8818-8316)
- Yasuhiro Gotô (ORCID: https://orcid.org/0000-0003-2235-8567)
- Masami Miyata
- Toshiyuki Washizawa
- Kazuyoshi Imaizumi (ORCID: https://orcid.org/0000-0002-3790-8691)
- Shuhei Shibata
- Takashi Kanno (ORCID: https://orcid.org/0009-0005-0488-1444)
- Daisuke Niwa
Institutions
- Fujita Health University (JP)
Publication Details
- Journal
- PubMed
- Published
- 2025-08-01
- DOI
- https://doi.org/10.20407/fmj.2024-027
- Primary Topic
- Chronic Obstructive Pulmonary Disease (COPD) Research
- Type
- article
- Field-Weighted Citation Impact
- 0.00