Deep learning-assisted diagnosis of femoral trochlear dysplasia based on magnetic resonance imaging measurements

doi:10.12998/wjcc.v11.i7.1477

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World Journal of Clinical Cases

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Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA

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World J Clin Cases. Mar 6, 2023; 11(7): 1477-1487
Published online Mar 6, 2023. doi: 10.12998/wjcc.v11.i7.1477

Table 5 Intragroup correlation coefficient and 95% confidence interval of the measures for the junior doctors, intermediate doctors and artificial intelligence models compared with senior doctors

Group	Trochlear depth (mm)	Asymmetry of the facet length	Lateral trochlear inclination (°)
Junior doctor	0.87 (0.78-0.92)^a	0.57 (0.32-0.73)^a	0.82 (0.75-0.88)^a
Intermediate doctor	0.88 (0.82-0.90)^a	0.41 (0.16-0.60)^a	0.87 (0.79-0.92)^a
Artificial intelligence model	0.91 (0.86-0.94)^a	0.71 (0.59-0.80)^a	0.91 (0.87-0.94)^a

^aP < 0.001.

Citation: Xu SM, Dong D, Li W, Bai T, Zhu MZ, Gu GS. Deep learning-assisted diagnosis of femoral trochlear dysplasia based on magnetic resonance imaging measurements. World J Clin Cases 2023; 11(7): 1477-1487
URL: https://www.wjgnet.com/2307-8960/full/v11/i7/1477.htm
DOI: https://dx.doi.org/10.12998/wjcc.v11.i7.1477