Google Research·· 2026-08-17
Seeing beyond BMI: Estimating cardiometabolic risk with smartphone imagery
Seeing beyond BMI: Estimating cardiometabolic risk with smartphone imagery
AI summary
Google Research proposed PhotoScan, a deep learning framework that estimates body fat percentage, A/G ratio and V/S ratio from ordinary 2D phone photos to predict insulin resistance.
Selection record
Threshold 60Official, first-handFirst 62Second 62
AdmittedSum of both 124 ≥ twice the threshold 120
- Source tier
- Official, first-hand; this tier's threshold is 60
- Pre-filter
- passed：深度学习框架从手机照片估计体成分
- Why it was chosen
- Shows how phone-photo body composition estimates and insulin resistance predictions compare in accuracy with DXA and BIA.
A model scores each item twice, independently, against one written standard, out of 100. An item is admitted only when the two scores add up to twice the threshold. The threshold is set per source tier.
Source: Google Research · research.google