Google Research· ResearchResearch paper

Seeing beyond BMI: Estimating cardiometabolic risk with smartphone imagery

Google Research introduces PhotoScan, a deep learning framework that estimates body composition metrics (body fat percentage, A/G ratio, V/S ratio) from standard 2D smartphone photos, achieving accuracy comparable to DXA scans for predicting insulin resistance.

From the source

PhotoScan demonstrates higher body fat percentage accuracy than smartwatch-based bioelectrical impedance analysis (BIA) sensors while unlocking A/G and V/S ratios beyond BIA's capabilities, offering a scalable, non-invasive framework to predict insulin resistance with near-DXA accuracy.

research.google

Announced

17 Aug 2026 10:34 UTC