Publication: PhenoScore: AI-based phenomics to quantify rare disease and genetic variation
PhenoScore: AI-based phenomics to quantify rare disease and genetic variation
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Dingemans, A. J. M., Hinne, M., Truijen, K. M. G., Goltstein, L., et al, & Rauch, A. (2022). PhenoScore: AI-based phenomics to quantify rare disease and genetic variation (No. 22281480; MedRxiv). https://doi.org/10.1101/2022.10.24.22281480
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While both molecular and phenotypic data are essential when interpreting genetic variants, prediction scores (CADD, PolyPhen, and SIFT) have focused on molecular details to evaluate pathogenicity — omitting phenotypic features. To unlock the full potential of phenotypic data, we developed PhenoScore: an open source, artificial intelligence-based phenomics framework. PhenoScore combines facial recognition technology with Human Phenotype Ontology (HPO) data analysis to quantify phenotypic similarity at both the level of individual patie
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Dingemans, A. J. M., Hinne, M., Truijen, K. M. G., Goltstein, L., et al, & Rauch, A. (2022). PhenoScore: AI-based phenomics to quantify rare disease and genetic variation (No. 22281480; MedRxiv). https://doi.org/10.1101/2022.10.24.22281480
