Facial photographs reveal mortality risk beyond triage

Abstract Rapid risk stratification is essential in the clinic, yet vital signs, laboratory tests, and triage scores may not fully capture risk at presentation. We investigated whether facial photographs taken after emergency admission provide an additional mortality signal. Using 27,660 smartphone facial photographs, we trained deep neural networks to identify mortality risk with a Cox proportional hazards framework. Face-derived risk scores strongly stratified short- and long-term mortality, outperforming triage levels, vital signs, blood chemistry, and facial age estimation. Face scores revealed substantial heterogeneity in risk within each triage category, including low-acuity patients with mortality risk exceeding that of high-acuity levels. Combining high-acuity triage with high face score quartiles identified patients with a sixty-fold increased mortality risk within 30 days (odds ratio 60.43 vs lowest risk and triage), while triage alone resulted in six-fold increase in mortality (odds ratio 6.05 vs lowest triage). Integrating facial risk scores with routine clinical variables further improved risk stratification. These findings indicate that unstructured facial photographs encode clinically actionable risk and may augment existing triage and monitoring strategies.