Enhancing deep learning models for predicting smoking Status using clinical data in patients with chronic obstructive pulmonary disease

Incorporating behavioral and psychosocial data enabled the models to capture complex smoking patterns while maintaining interpretability. These findings emphasize the value of multidimensional data in identifying high-risk individuals and informing targeted smoking cessation strategies in COPD care. Future research should include synthesized behavioral variables often absent from large external datasets and validate model performance in more diverse populations.