BAYESIAN CAUSAL RELATIONSHIP NETWORK MODELS FOR HEALTHCARE DIAGNOSIS AND TREATMENT BASED ON PATIENT DATA

摘要

BAYESIAN CAUSAL RELATIONSHIP NETWORK MODELS FOR HEALTHCARE DIAGNOSIS AND TREATMENT BASED ON PATIENT DATA Systems, methods, and computer-readable medium are provided for healthcare analysis. Data corresponding to a plurality of patients is received. The data is parsed to generate normalized data for a plurality of variables, with normalized data generated for more than one variable for each patient. A causal relationship network model is generated relating the plurality of variables based on the generated normalized data using a Bayesian network algorithm. The causal relationship network model includes variables related to a plurality of medical conditions or medical drugs. In another aspect, a selection of a medical condition or drug is received. A sub- network is determined from a causal relationship network model. The sub-network includes one or more variables associated with the selected medical condition or drug. One or more predictors for the selected medical condition or drug are identified. [Figure 2]