DEEP LEARNING ALGORITHMS SHOW SOME POTENTIAL AS AN ADJUNCTIVE TOOL IN CARIES DIAGNOSIS

LeCun, 2015, Deep learning, Nature, 521, 436, 10.1038/nature14539 Hwang, 2019, An overview of deep learning in the field of dentistry, Imaging Sci Dent, 49, 1, 10.5624/isd.2019.49.1.1 Goecks, 2020, How machine learning will transform biomedicine, Cell, 181, 92, 10.1016/j.cell.2020.03.022 Corbella, 2021, Applications of deep learning in dentistry, Oral Surg Oral Med Oral Pathol Oral Radiol, 132, 225, 10.1016/j.oooo.2020.11.003 Wenzel, 2021, Radiographic modalities for diagnosis of caries in a historical perspective: from film to machine-intelligence supported systems, Dentomaxillofac Radiol, 50, 10.1259/dmfr.20210010 Yousef, 2022, A holistic overview of deep learning approach in medical imaging, Multimed Syst, 28, 881, 10.1007/s00530-021-00884-5 Sounderajah, 2021, Developing a reporting guideline for artificial intelligence-centred diagnostic test accuracy studies: the STARD-AI protocol, BMJ Open, 11, 10.1136/bmjopen-2020-047709 Norgeot, 2020, Minimum information about clinical artificial intelligence modeling: the MI-CLAIM checklist, Nat Med, 26, 1320, 10.1038/s41591-020-1041-y Landerdahl Stridsberg, 2022, Gray literature in evaluating effectiveness in digital health and health and welfare technology: a source worth considering, J Med Internet Res, 24, e29307, 10.2196/29307