Development of a deep learning model to predict smoking status in patients with chronic obstructive pulmonary disease: A secondary analysis of cross-sectional national survey
This deep learning model accurately predicts smoking status in patients with COPD, offering potential as a decision-support tool to detect high-risk persistent smokers for targeted interventions. Future studies should focus on external validation and incorporate additional behavioral and psychological variables to improve its generalizability and performance.
Authors
- Sehyun Cho (ORCID: https://orcid.org/0000-0003-1797-7523)
- Ja Yun Choi (ORCID: https://orcid.org/0000-0002-1284-250X)
- Sudarshan Pant (ORCID: https://orcid.org/0000-0002-2385-9673)
- Hyung-Jeong Yang (ORCID: https://orcid.org/0000-0003-3024-5060)
- Eui-Jeong Ryu
Institutions
- Chonnam National University (KR)
- Dongshin University (KR)
Publication Details
- Journal
- Digital Health
- Published
- 2025-04-01
- DOI
- https://doi.org/10.1177/20552076251333660
- Citations
- 3
- Primary Topic
- Chronic Obstructive Pulmonary Disease (COPD) Research
- Type
- article
- Field-Weighted Citation Impact
- 4.56
Funders
- National Research Foundation of Korea