Detecting time-evolving phenotypic topics via tensor factorization on electronic health records: Cardiovascular disease case study

Present a method using Tensor Factorization to find subphenotypes from longitudinal EHR. We applied this approach to 12,380 patients' 10-year PheCodes prior to CVD. We identified 14 subphenotypes and showed the progress pattern. Topics Vitamin D deficiency, Urinary infections cannot be explained by traditional risk factors. Discovering subphenotypes of complex diseases can help characterize disease cohorts for investigative studies aimed at developing better diagnoses and treatments.