Identification of osteoporosis using ensemble deep learning model with panoramic radiographs and clinical covariates.

ABSTRACT: Osteoporosis is becoming a global health issue due to increased life expectancy. However, it is difficult to detect in its early stages owing to a lack of discernible symptoms. Hence, screening for osteoporosis with widely used dental panoramic radiographs would be very cost-effective and useful. In this study, we investigate the use of deep learning to classify osteoporosis from dental panoramic radiographs. In addition, the effect of adding clinical covariate data to the radiographic images on the identification performance was assessed. For objective labeling, a dataset containing 778 images was collected from patients who underwent both skeletal-bone-mineral density measurement and dental panoramic radiography at a single general hospital between 2014 and 2020. Osteoporosis was assesse

SUBMITTER: Sukegawa S 

PROVIDER: S-EPMC9005660 | biostudies-literature | 2022 Apr

REPOSITORIES: biostudies-literature