Artificial Intelligence for Caries Detection: Value of Data and Information.

ABSTRACT: If increasing practitioners' diagnostic accuracy, medical artificial intelligence (AI) may lead to better treatment decisions at lower costs, while uncertainty remains around the resulting cost-effectiveness. In the present study, we assessed how enlarging the data set used for training an AI for caries detection on bitewings affects cost-effectiveness and also determined the value of information by reducing the uncertainty around other input parameters (namely, the costs of AI and the population's caries risk profile). We employed a convolutional neural network and trained it on 10%, 25%, 50%, or 100% of a labeled data set containing 29,011 teeth without and 19,760 teeth with caries lesions stemming from bitewing radiographs. We employed an established health economic modeling and analyti

SUBMITTER: Schwendicke F 

PROVIDER: S-EPMC9516598 | biostudies-literature | 2022 Oct

REPOSITORIES: biostudies-literature