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Artificial intelligence supported facial feature analysis in medical genetics
1Nemours Children's Health, Wilmington, Delaware, USA.
Purpose Of Review:
This review highlights recent developments in the use of machine learning supported facial feature analysis in the context of genetic and syndromic conditions. The review focusses on 2D image-based tools. The 2D images are easily obtained using handheld devices such as mobile phones and are more relevant to general practice than 3D image based systems.
Recent Findings:
Different algorithms are used widely in pediatric clinics, medical genetics clinics, for gene variant analysis and in research. Integrated systems combining next-generation phenotyping with next-generation genotyping support a shortened diagnostic odyssey for patients.
Summary:
Future integration of phenotyping using data available in electronic medical records with genotyping data will likely result in earlier identification of possible genetic conditions.
