{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,23]],"date-time":"2025-06-23T10:45:06Z","timestamp":1750675506578},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643683881","type":"print"},{"value":"9781643683898","type":"electronic"}],"license":[{"start":{"date-parts":[[2023,5,18]],"date-time":"2023-05-18T00:00:00Z","timestamp":1684368000000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/2.zoppoz.workers.dev:443\/https\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,5,18]]},"abstract":"<jats:p>Computer vision has useful applications in precision medicine and recognizing facial phenotypes of genetic disorders is one of them. Many genetic disorders are known to affect faces\u2019 visual appearance and geometry. Automated classification and similarity retrieval aid physicians in decision-making to diagnose possible genetic conditions as early as possible. Previous work has addressed the problem as a classification problem; however, the sparse label distribution, having few labeled samples, and huge class imbalances across categories make representation learning and generalization harder. In this study, we used a facial recognition model trained on a large corpus of healthy individuals as a pre-task and transferred it to facial phenotype recognition. Furthermore, we created simple baselines of few-shot meta-learning methods to improve our base feature descriptor. Our quantitative results on GestaltMatcher Database (GMDB) show that our CNN baseline surpasses previous works, including GestaltMatcher, and few-shot meta-learning strategies improve retrieval performance in frequent and rare classes.<\/jats:p>","DOI":"10.3233\/shti230312","type":"book-chapter","created":{"date-parts":[[2023,5,19]],"date-time":"2023-05-19T08:48:54Z","timestamp":1684486134000},"source":"Crossref","is-referenced-by-count":5,"title":["Few-Shot Meta-Learning for Recognizing Facial Phenotypes of Genetic Disorders"],"prefix":"10.3233","author":[{"given":"\u00d6mer","family":"S\u00fcmer","sequence":"first","affiliation":[{"name":"Chair for Human-Centered Artificial Intelligence, University of Augsburg, Germany"}]},{"given":"Fabio","family":"Hellmann","sequence":"additional","affiliation":[{"name":"Chair for Human-Centered Artificial Intelligence, University of Augsburg, Germany"}]},{"given":"Alexander","family":"Hustinx","sequence":"additional","affiliation":[{"name":"Institute for Genomic Statistics and Bioinformatics, University of Bonn, Germany"}]},{"given":"Tzung-Chien","family":"Hsieh","sequence":"additional","affiliation":[{"name":"Institute for Genomic Statistics and Bioinformatics, University of Bonn, Germany"}]},{"given":"Elisabeth","family":"Andr\u00e9","sequence":"additional","affiliation":[{"name":"Chair for Human-Centered Artificial Intelligence, University of Augsburg, Germany"}]},{"given":"Peter","family":"Krawitz","sequence":"additional","affiliation":[{"name":"Institute for Genomic Statistics and Bioinformatics, University of Bonn, Germany"}]}],"member":"7437","container-title":["Studies in Health Technology and Informatics","Caring is Sharing \u2013 Exploiting the Value in Data for Health and Innovation"],"original-title":[],"link":[{"URL":"https:\/\/2.zoppoz.workers.dev:443\/https\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/SHTI230312","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,5,31]],"date-time":"2023-05-31T15:02:50Z","timestamp":1685545370000},"score":1,"resource":{"primary":{"URL":"https:\/\/2.zoppoz.workers.dev:443\/https\/ebooks.iospress.nl\/doi\/10.3233\/SHTI230312"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,5,18]]},"ISBN":["9781643683881","9781643683898"],"references-count":0,"URL":"https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.3233\/shti230312","relation":{},"ISSN":["0926-9630","1879-8365"],"issn-type":[{"value":"0926-9630","type":"print"},{"value":"1879-8365","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,5,18]]}}}