# AI tool predicts cancer patients’ survival chances from facial photos

> US researchers create AI tool using facial photos to predict cancer survival rates.
- Title: AI tool predicts cancer patients’ survival chances from…
- Summary: US researchers create AI tool using facial photos to predict cancer survival rates. US researchers developed AI tools that analyze facial features to…
- Keywords: faahr-facesurvival, faahr-faceage, cancer survival, biological age, mass general brigham, the lancet digital health, news, world, tool, predicts, cancer, patients
- Source: Malay Mail — https://malaymail.com/news/life/2026/10/21/ai-tool-predicts-cancer-patients-survival-chances-from-facial-photos-study-finds/240047
- Published: 2026-10-21T21:00:00+00:00
- Read time: 1 min
- Topics: faahr-facesurvival, faahr-faceage, cancer survival, biological age, mass general brigham, the lancet digital health, news, world
## AI tool predicts cancer survival
US researchers developed AI tools to predict cancer patients' survival chances from facial photographs.

> US researchers have created AI tools to predict cancer patients' survival chances and biological age from facial photographs, reported in The Lancet Digital Health
## Models analyze facial features
The tools, FAHR-FaceAge and FAHR-FaceSurvival, analyse facial features to estimate biological age and predict cancer survival.

> The model was trained on more than 40 million facial photos and adapted into two tools: FAHR-FaceAge, which estimates biological age, and FAHR-FaceSurvival, which predicts cancer patients’ survival directly from facial images without relying on age estimates
## Survival model focuses on key areas
The survival model focused mainly on areas beneath the eyes and around the nose.

> Researchers found that the survival model focused mainly on areas beneath the eyes and around the nose, while the age-estimation model examined facial features around the mouth and temples
## Age-estimation model examines features
The age-estimation model examined facial features around the mouth and temples.

> Researchers found that the survival model focused mainly on areas beneath the eyes and around the nose, while the age-estimation model examined facial features around the mouth and temples
## Training and validation data
The survival model was trained on 34,363 patients and tested on 3,820 images, with independent validation using 4,892 cancer patients in the Netherlands.

> The survival model was trained on images of 34,363 patients and tested on another 3,820, with results independently validated using data from 4,892 cancer patients in the Netherlands
## Risk differences in patients
Patients in the highest-risk group had more than three times the mortality risk of those in the lowest-risk group.

> Researchers found that patients classified in the highest-risk group had more than three times the mortality risk of those in the lowest-risk group, even after accounting for clinical factors
## Age appearance affects survival
Patients whose faces appeared at least five years older than their actual age had a 21 per cent higher mortality risk.

> Patients whose faces appeared at least five years older than their actual age also had a 21 per cent higher mortality risk, while those appearing at least five years younger had a 17 per cent lower risk
## Key takeaway

US researchers developed AI tools that analyze facial features to estimate cancer patients' survival chances and biological age, with higher accuracy when combined.