A hyperspectral facial analysis system and method for personalized health scoring to assess the risk that a person has a disease. Embodiments capture images in multiple spectral bands, such as visible, infrared, and ultraviolet, and analyze these images to generate multiple health metrics, such as pallor, temperature, sweat, and chromophores. These metrics may be combined into an overall health score that may be used for screening. Image analysis may focus on the area under the eyes, where skin is thinnest. Images may be compared to a reference population to identify anomalous values, so that health scoring automatically adjusts for local conditions. Pallor may be calculated based on hue and saturation of visible light images. Temperature may be calculated based on infrared image intensity. Sweat may be calculated using cross-polarized images to identify specular highlights. Chromophores may be calculated by comparing frequency domain ultraviolet images to those of the reference population.