Efficiency of Computer-Aided Facial Phenotyping (DeepGestalt) in Individuals With and Without a Genetic Syndrome: Diagnostic Accuracy Study

Journals

1. Dunkel L, Fernandez-Luque L, Loche S, Savage M. Digital technologies to improve the precision of paediatric growth disorder diagnosis and management. Growth Hormone & IGF Research 2021;59:101408 View
2. Hong D, Zheng Y, Xin Y, Sun L, Yang H, Lin M, Liu C, Li B, Zhang Z, Zhuang J, Qian M, Wang S. Genetic syndromes screening by facial recognition technology: VGG-16 screening model construction and evaluation. Orphanet Journal of Rare Diseases 2021;16(1) View
3. Katsanis S, Claes P, Doerr M, Cook-Deegan R, Tenenbaum J, Evans B, Lee M, Anderton J, Weinberg S, Wagner J, Sane R. A survey of U.S. public perspectives on facial recognition technology and facial imaging data practices in health and research contexts. PLOS ONE 2021;16(10):e0257923 View
4. Attallah O. A deep learning-based diagnostic tool for identifying various diseases via facial images. DIGITAL HEALTH 2022;8:205520762211244 View
5. Pascolini G, Gaudioso F, Baldi M, Alario D, Dituri F, Novelli A, Baban A. Facial clues to the photosensitive trichothiodystrophy phenotype in childhood. Journal of Human Genetics 2023 View
6. D’Souza A, Ryan E, Sidransky E. Facial features of lysosomal storage disorders. Expert Review of Endocrinology & Metabolism 2022;17(6):467 View
7. Hsieh T, Bar-Haim A, Moosa S, Ehmke N, Gripp K, Pantel J, Danyel M, Mensah M, Horn D, Rosnev S, Fleischer N, Bonini G, Hustinx A, Schmid A, Knaus A, Javanmardi B, Klinkhammer H, Lesmann H, Sivalingam S, Kamphans T, Meiswinkel W, Ebstein F, Krüger E, Küry S, Bézieau S, Schmidt A, Peters S, Engels H, Mangold E, Kreiß M, Cremer K, Perne C, Betz R, Bender T, Grundmann-Hauser K, Haack T, Wagner M, Brunet T, Bentzen H, Averdunk L, Coetzer K, Lyon G, Spielmann M, Schaaf C, Mundlos S, Nöthen M, Krawitz P. GestaltMatcher facilitates rare disease matching using facial phenotype descriptors. Nature Genetics 2022;54(3):349 View
8. Mensah M, Ott C, Horn D, Pantel J. A machine learning-based screening tool for genetic syndromes in children. The Lancet Digital Health 2022;4(5):e295 View
9. Mahdi S, Matthews H, Nauwelaers N, Vanneste M, Gong S, Bouritsas G, Baynam G, Hammond P, Spritz R, Klein O, Hallgrimsson B, Peeters H, Bronstein M, Claes P. Multi-Scale Part-Based Syndrome Classification of 3D Facial Images. IEEE Access 2022;10:23450 View
10. Porras A, Rosenbaum K, Tor-Diez C, Summar M, Linguraru M. A machine learning-based screening tool for genetic syndromes in children – Authors' reply. The Lancet Digital Health 2022;4(5):e296 View
11. Park S, Kim J, Song T, Jang D. Case Report: The success of face analysis technology in extremely rare genetic diseases in Korea: Tatton–Brown–Rahman syndrome and Say–Barber –Biesecker–Young–Simpson variant of ohdo syndrome. Frontiers in Genetics 2022;13 View
12. Ciancia S, Goedegebuure W, Grootjen L, Hokken-Koelega A, Kerkhof G, van der Kaay D. Computer-aided facial analysis as a tool to identify patients with Silver–Russell syndrome and Prader–Willi syndrome. European Journal of Pediatrics 2023 View