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KMID : 1151120230310040271
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Annals of Child Neurology
2023 Volume.31 No. 4 p.271 ~ p.275
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Lessons Learned from the Point-of-Care Use of a Facial Analysis Technology
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Kim Jon-Soo
Ko Han-Sol
Woo Hye-Won
Kim Won-Seop
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Abstract
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Purpose : We aimed to evaluate the utility of facial analysis technology for genetic diagnoses in a typical pediatric genetic clinic.
Methods : A retrospective review identified children (aged <18 years) who had not previously received a definitive genetic diagnosis and underwent a comprehensive genetic evaluation. Their photographs and relevant clinical non-facial features were uploaded to the CLINIC application of the Face2Gene web interface, and the resulting analysis was accessed and correlated to the molecular diagnosis.
Results : Of the 23 children included, the overall diagnostic yield in this study was 60.9% (14/23). In total, 64.3% of patients had the correct condition suggested in the top 10 differential diagnoses. The gestalt similarity was only 55.6%, but the phenotypic features added by the clinician showed a similarity of more than the medium level in all patients.
Conclusion : Our data underscore the usefulness of facial analysis technology as an auxiliary point-of-care tool in pediatric genetic clinics, and we also present some considerations to increase accuracy.
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KEYWORD
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Face, Genetic techniques, Machine learning
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