Artificial Intelligence Platform for Dental Claims Adjudication Prediction Based on Radiographic Clinical Findings

摘要

Patient meta information, narratives, charts, and images are processed according to a first machine learning model to determine hidden features relating to the adjudication outcome of a proposed claim packet. Image are concatenated and processed using a second machine learning model to label anatomy including periodontal, endodontic, restorative, orthodontic, decay, and other general clinical findings. The meta information, anatomy labels, and image are concatenated and processed using a third machine learning model to obtain feature measurements, such as decay quantifications and periodontal measurements. The feature measurements, anatomy labels, teeth labels, and image information may be concatenated and input to a fourth machine learning model to obtain a diagnosis for a periodontal, decay, endodontic, orthodontic, or restorative condition. Feature measurements and/or the diagnosis may be processed according to a diagnosis hierarchy to determine whether a treatment is appropriate, and the most probable claim adjudication outcome.