Artificial intelligence supported facial feature analysis in medical genetics

Abstract

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.

Keywords: artificial intelligence tools; machine learning supported facial feature analysis; next-generation phenotyping.