A classification algorithm to predict chronic pain using both regression and machine learning - A stepwise approach.

ABSTRACT: This secondary data analysis study aimed to (1) investigate the use of two sense-based parameters (movement and sleep hours) as predictors of chronic pain when controlling for patient demographics and depression, and (2) identify a classification model with accuracy in predicting chronic pain. Data collected by Oregon Health & Science University between March 2018 and December 2019 under the Collaborative Aging Research Using Technology Initiative were analyzed in two stages. Data were collected by sensor technologies and questionnaires from older adults living independently or with a partner in the community. In Stage 1, regression models were employed to determine unique sensor-based behavioral predictors of pain. These sensor-based parameters were used to create a classification model t

SUBMITTER: Tsai PF 

PROVIDER: S-EPMC8906500 | biostudies-literature | 2021 Dec

REPOSITORIES: biostudies-literature