ArticleIndian journal of pediatrics2026
The Utility of Face2Gene App for Syndrome Recognition in Indian Children with Dysmorphism.
Article in Indian journal of pediatrics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- The Utility of Face2Gene App for Syndrome Recognition in Indian Children with Dysmorphism: Correspondence.Indian journal of pediatrics · 2026Article
- The Utility of Face2Gene App for Syndrome Recognition in Indian Children with Dysmorphism: Author's Reply.Indian journal of pediatrics · 2026Article
Corrections and comments
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Authors and funding
17 authors.
Funding
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Abstract
objectivesTo determine the accuracy of Face2Gene (F2G) app in the diagnosis of a genetic syndrome as a first correct response, after uploading the image of the patient in the app (top 1 accuracy), first 3 responses (top 3 accuracy), and first 10 responses (top 10 accuracy) out of 30 differential diagnoses given by the app. Also, to determine the accuracy of the app for rare and ultra-rare diagnoses given by the app.
methodsFrontal facial images of individuals with the diagnosis of a genetic syndrome (established clinically or molecularly) were analysed with and without additional clinical features.
resultsIn this study, a total of 118 children were recruited. Overall, the molecularly confirmed eventual diagnosis appeared in the "top 10" suggested syndromes by Face2Gene in 75/118 cases, providing a diagnostic yield of 63.6%. In this study, the top 1 accuracy for correct first diagnosis by the app and clinician's first diagnosis was 45.8% (n = 54). The Mcnemar test was examined for the clinician's accurate diagnosis as compared to top 1, top 3, and top 10 accuracy by the app and the p-value was statistically significant for top 10 accuracy (0.0005) and not for the top 1 and 3 diagnoses. The top 10 accuracy for the app in the rare cases was 21/30 cases (70%), and for ultra-rare cases was 28/64 (43.8%).
conclusionsThe Face2Gene app is useful as an assistant to clinicians in the diagnosis of rare and ultra-rare diseases. The top 10 accuracy is better than clinical diagnosis, and the yield is better for the ultra-rare cases and the single gene disease category, too.
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