Researchers are developing an artificial intelligence (AI) system that can help improve diagnosis of rare genetic diseases through facial analysis.
The underlying hereditary mutations in rare genetic diseases often cause varying degrees of impairment in different areas of the body. In most cases, these hereditary changes are also expressed by characteristic facial features, though this varies from disease to disease. Artificial intelligence (AI) uses these facial characteristics, calculates the similarities, and automatically links them to clinical symptoms and genetic data of patients.
The AI system “GestaltMatcher” described in the current publication is a continued development of another AI system: “DeepGestalt”. The Institute for Genomic Statistics and Bioinformatics (IGSB) team—at the University Hospital Bonn in Germany—developed and trained DeepGestalt with other institutions a few years ago.
While DeepGestalt still required about ten non-related affected persons as a reference for system training, its successor “GestaltMatcher” requires significantly fewer patients for feature matching.
“The goal is to detect such diseases at an early stage and initiate appropriate therapy as soon as possible,” says professor Peter Krawitz, MD, PhD, from the IGSB at the University Hospital Bonn in Germany. Krawitz is a member of the Cluster of Excellence ImmunoSensation2 and the Transdisciplinary Research Area “Modelling” at the University of Bonn.
Furthermore, the new AI system also considers similarities with patients who have also not yet been diagnosed, and thus combinations of characteristics that have not yet been described. GestaltMatcher therefore also “recognizes” diseases that were previously unknown to it and suggests diagnoses based on this.
“This means we can now classify previously unknown diseases, search for other cases and provide clues as to the molecular basis,” says Krawitz.
The team used 17,560 patient photos, most of which came from digital health company FDNA, which the research team worked with developing the web service through which the AI can be used. Around 5,000 of the photos and patient data were contributed by the research team at the Institute of Human Genetics at the University of Bonn, along with nine other university sites in Germany and abroad.
The researchers focused on disease patterns that were as diverse as possible. They were able to consider a total of 1,115 different rare diseases.
“This wide variation in appearance trained the AI so well that we can now diagnose with relative confidence even with only two patients as our baseline at best, if that’s possible,” Krawitz says.
Krawitz and his team turned over the data they collected themselves to the non-profit Association for Genome Diagnostics (AGD), to provide researchers with access.
“The GestaltMatcher Database (GMDB) will improve the comparability of algorithms and provide the basis for further development of artificial intelligence for rare diseases, including other medical image data such as X-rays or retinal images from ophthalmology,” Krawitz says.
Featured image: The image shows matches, an allusion to matching facial features and diseases. A gene sequence is also burned onto the matches. This encryption contains the title and the authors of the study. The blue match heads symbolize rare diseases. Photo: Jean Tori Pantel
