Deep Learning and Computer Vision
Deep learning algorithms build syndrome-specific computational-based classifiers (syndrome gestalts) Proprietary technology converts a patient photo into de-identified mathematical facial descriptors (facial descriptors) The patient’s facial descriptor is compared to syndrome gestalts to quantify similarity (gestalt scores) resulting in a prioritized list of syndromes with similar morphology Artificial intelligence suggests likely phenotypic traits and genes to assist in feature annotation and syndrome prioritization. Please read more in this Nature Medicine publication.
Real World Phenotype Data
Crowd-sourced by expert genetics professionals, labs & bioinformatics from real patients Millions of comprehensive, precise & accurate data points Learning system uses expansive data for unique health insights and genomics discoveries
Variant Prioritization Technologies
Open-source API allows labs to pull phenotypic information securely. The combination of the gestalt scores and the annotated features highlights clinically-significant variants for better interpretation.