A Multimodal Deep Learning Approach to Predicting Systemic Diseases from Oral Conditions.

ABSTRACT: Background: It is known that oral diseases such as periodontal (gum) disease are closely linked to various systemic diseases and disorders. Deep learning advances have the potential to make major contributions to healthcare, particularly in the domains that rely on medical imaging. Incorporating non-imaging information based on clinical and laboratory data may allow clinicians to make more comprehensive and accurate decisions. Methods: Here, we developed a multimodal deep learning method to predict systemic diseases and disorders from oral health conditions. A dual-loss autoencoder was used in the first phase to extract periodontal disease-related features from 1188 panoramic radiographs. Then, in the second phase, we fused the image features with the demographic data and clinical informat

SUBMITTER: Zhao D 

PROVIDER: S-EPMC9777898 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature