{"title":"Lessons Learned from the Point-of-Care Use of a Facial Analysis Technology","authors":"Jon Soo Kim, Hansol Ko, Hyewon Woo, Won Seop Kim","doi":"10.26815/acn.2023.00227","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":33305,"journal":{"name":"Annals of Child Neurology","volume":"27 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Annals of Child Neurology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.26815/acn.2023.00227","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Medicine","Score":null,"Total":0}
引用次数: 0
Abstract
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.