Foundation Artificial Intelligence Models for Health Recognition Using Face Photographs (FAHR-Face)
FAHR-Face is a foundation model trained on >40 million facial images and fine-tuned for two tasks: biological age estimation (FAHR-FaceAge) and survival risk prediction (FAHR-FaceSurvival). FAHR-FaceAge achieved a mean absolute error of 5.1 years on public datasets and outperformed benchmark models across the full human lifespan. FAHR-FaceSurvival demonstrated robust mortality prediction, with the highest-risk quartile showing more than triple the mortality of the lowest (adjusted HR 3.22; P<0.001). The combination of both models improved prognostic accuracy. Deployed at faceage.bwh.harvard.edu.
Citation
Haugg F, Lee G, He J, Nürnberg L, Bontempi D, Bitterman DS, Catalano P, Prudente V, Glubokov D, Warrington A, Pai S, De Ruysscher D, Guthier C, Kann BH, Gladyshev VN, Aerts HJWL, Mak RH. Foundation Artificial Intelligence Models for Health Recognition Using Face Photographs (FAHR-Face). arXiv:2506.14909. 2025.