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🔬TODAY’S BREAKTHROUGH
A new study introduces a foundation AI model capable of predicting biological age and survival risk directly from facial photographs, bringing scalable, non‑invasive biomarkers into reach.
The Discovery:
Researchers developed FAHR‑Face, a deep learning model trained on over 40 million faces, fine‑tuned for estimating biological (epigenetic) age and survival risk. It achieved high accuracy and proved robust across variables such as lighting, makeup, and pose.
The Science:
FAHR‑FaceAge estimates biological age from facial images using deep neural networks.
FAHR‑FaceSurvival predicts survival risk validated on over 34,000 cancer‑patient photos using Cox regression models
Model evaluation confirmed resilience to cosmetic variation, including surgical alteration, light, and makeup.
This system offers a new, non‑invasive biomarker approach linking appearance to healthspan and mortality risk.
Your Action:
Consider using facial bio‑age predictions only as exploratory tools, confirm with clinical measures. Prioritize evidence‑backed actions like exercise, diet, sleep, stress reduction. Approach any AI health app with caution for now.
Bottom Line:
FAHR‑Face offers a novel, scalable method to infer biological age and survival risk from images, paving the way for non‑invasive aging biomarkers.
Source:
Foundation Artificial Intelligence Models for Health Recognition Using Face Photographs, arXiv preprint, Haugg et al., June 17 2025
https://arxiv.org/abs/2506.14909
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Disclaimer:
This newsletter is for informational purposes only and does not substitute professional medical advice. Always consult with a healthcare provider before making any changes to your health regimen.