Statistical validation of a deep learning algorithm for dental anomaly detection in intraoral radiographs using paired data

arXiv:2402.14022v1 Announce Type: cross
Abstract: This article describes the clinical validation study setup, statistical analysis and results for a deep learning algorithm which detects dental anomalies in intraoral radiographic images, more specifically caries, apical lesions, root canal treatment defects, marginal defects at crown restorations, periodontal bone loss and calculus. The study compares the detection performance of dentists using the deep learning algorithm to the prior performance of these dentists evaluating the images without algorithmic assistance. Calculating the marginal profit and …

abstract algorithm analysis anomaly anomaly detection article arxiv clinical cs.cv cs.lg data deep learning defects dental detection eess.iv images setup stat.ap statistical study treatment type validation