دورية أكاديمية

GestaltMatcher facilitates rare disease matching using facial phenotype descriptors.

التفاصيل البيبلوغرافية
العنوان: GestaltMatcher facilitates rare disease matching using facial phenotype descriptors.
المؤلفون: Hsieh, T.C., Bar-Haim, A., Moosa, S., Ehmke, N., Gripp, K.W., Pantel, J.T., Danyel, M., Mensah, M.A., 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., Kruger, E., Küry, S., Bézieau, S., Schmidt, A., Peters, S., Engels, H., Mangold, E., Kreiß, M., Cremer, K., Perne, C., Betz, R.C., Bender, T., Grundmann-Hauser, K., Haack, T.B., Wagner, M., Brunet, T., Bentzen, H.B., Averdunk, L., Coetzer, K.C., Lyon, G.J., Spielmann, M., Schaaf, C.P., Mundlos, S., Nöthen, M.M., Krawitz, P.M.
المصدر: Nat. Genet. 54, 349-357 (2022)
بيانات النشر: Nature Portfolio
سنة النشر: 2022
المجموعة: PuSH - Publikationsserver des Helmholtz Zentrums München
الوصف: Many monogenic disorders cause a characteristic facial morphology. Artificial intelligence can support physicians in recognizing these patterns by associating facial phenotypes with the underlying syndrome through training on thousands of patient photographs. However, this ‘supervised’ approach means that diagnoses are only possible if the disorder was part of the training set. To improve recognition of ultra-rare disorders, we developed GestaltMatcher, an encoder for portraits that is based on a deep convolutional neural network. Photographs of 17,560 patients with 1,115 rare disorders were used to define a Clinical Face Phenotype Space, in which distances between cases define syndromic similarity. Here we show that patients can be matched to others with the same molecular diagnosis even when the disorder was not included in the training set. Together with mutation data, GestaltMatcher could not only accelerate the clinical diagnosis of patients with ultra-rare disorders and facial dysmorphism but also enable the delineation of new phenotypes.
نوع الوثيقة: article in journal/newspaper
وصف الملف: application/pdf
اللغة: English
تدمد: 1061-4036
1546-1718
العلاقة: info:eu-repo/semantics/altIdentifier/pmid/35145301; info:eu-repo/semantics/altIdentifier/wos/WOS:000753785800005; info:eu-repo/semantics/altIdentifier/isbn/1061-4036; info:eu-repo/semantics; https://push-zb.helmholtz-muenchen.de/frontdoor.php?source_opus=64310Test; urn:isbn:1061-4036; urn:issn:1061-4036; urn:issn:1546-1718
DOI: 10.1038/s41588-021-01010-x
الإتاحة: https://doi.org/10.1038/s41588-021-01010-xTest
https://push-zb.helmholtz-muenchen.de/frontdoor.php?source_opus=64310Test
حقوق: info:eu-repo/semantics/openAccess
رقم الانضمام: edsbas.E0D2DBDC
قاعدة البيانات: BASE
الوصف
تدمد:10614036
15461718
DOI:10.1038/s41588-021-01010-x