This paper presents a method to identify precise patterns of clinical disease from electronic health records, without supervision. It uses the principle of probabilistic independence to separate multiple overlapping disease signals present in patient data. Applying the method to 269,099 records with 9,195 variables, it produced 2,000 interpretable patterns of disease, i...