Machine learning application for predicting smoking cessation among US adults: An analysis of waves 1-3 of the PATH study

ABSTRACT: Identifying determinants of smoking cessation is critical for developing optimal cessation treatments and interventions. Machine learning (ML) is becoming more prevalent for smoking cessation success prediction in treatment programs. However, only individuals with an intention to quit smoking cigarettes participate in such programs, which limits the generalizability of the results. This study applies data from the Population Assessment of Tobacco and Health (PATH), a United States longitudinal nationally representative survey, to select primary determinants of smoking cessation and to train ML classification models for predicting smoking cessation among the general population. An analytical sample of 9,281 adult current established smokers from the PATH survey wave 1 was used to develop cl

SUBMITTER: Issabakhsh M 

PROVIDER: S-EPMC10249849 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature