Indermun, SuvarnaShaik, ShoayebNyirenda, ClementJohannes, KeithMulder, Riaan2024-05-152024-05-152023-09Indermun, S., Shaik, S., Nyirenda, C., Johannes, K. & Mulder, R. 2023, 'Human examination and artificial intelligence in cephalometric landmark detection—is AI ready to take over?', Dentomaxillofacial Radiology, vol. 52, no. 6, art. 20220362, pp. 1-14, doi : 10.1259/dmfr.20220362.0250-832X (print)1476-542X (online)10.1259/dmfr.20220362http://hdl.handle.net/2263/95993OBJECTIVES : To compare the precision of two cephalometric landmark identification methods, namely a computer-assisted human examination software and an artificial intelligence program, based on South African data. METHODS : This retrospective quantitative cross-sectional analytical study utilized a data set consisting of 409 cephalograms obtained from a South African population. 19 landmarks were identified in each of the 409 cephalograms by the primary researcher using the two programs [(409 cephalograms x 19 landmarks) x 2 methods = 15,542 landmarks)]. Each landmark generated two coordinate values (x, y), making a total of 31,084 landmarks. Euclidean distances between corresponding pairs of observations was calculated. Precision was determined by using the standard deviation and standard error of the mean. RESULTS : The primary researcher acted as the gold-standard and was calibrated prior to data collection. The inter- and intrareliability tests yielded acceptable results. Variations were present in several landmarks between the two approaches; however, they were statistically insignificant. The computer-assisted examination software was very sensitive to several variables. Several incidental findings were also discovered. Attempts were made to draw valid comparisons and conclusions. CONCLUSIONS : There was no significant difference between the two programs regarding the precision of landmark detection. The present study provides a basis to: (1) support the use of automatic landmark detection to be within the range of computer-assisted examination software and (2) determine the learning data required to develop AI systems within an African context.en© 2023 The Authors. Published by the British Institute of Radiology under the terms of the Creative Commons Attribution-NonCommercial 4.0 Unported License.CephalometryCephalometric landmarksOrthodonticsArtificial intelligence (AI)Article