Method and system for creating bayesian knowledge networks (bkns) for medical conditions

A system for creating Bayesian Knowledge Networks (BKNs) for medical conditions, the system comprising:

• a processor;
• and
• a memory communicatively coupled to the processor, wherein the memory stores processor-executable instructions, which, on execution, causes the processor to:
• retrieve an audit trail dataset from an Electronic Medical Record (EMR) corresponding to each of a plurality of patients for one or more medical conditions, wherein the audit trail dataset comprises a plurality of events;
• determine a generalized hospital event timeline for each of the one or more medical conditions based on the audit trail dataset, wherein the generalized hospital event timeline comprises a plurality of nodes corresponding to the plurality of events, and wherein the plurality of nodes is connected by unidirected edges in a chronological order of the plurality of events;
• generate a fully connected network of the plurality of nodes of one or more generalized hospital event timelines of the one or more medical conditions, wherein each two of the plurality of nodes in the fully connected network are interconnected via an undirected edge;
• determine a relation type corresponding to each two of the plurality of nodes of the fully connected network based on the one or more generalized hospital event timelines using a causal network learning algorithm;
• and
• create a BKN from the fully connected network based on the determined relation type for each two of the plurality of nodes.

A non-transitory computer-readable medium storing computer-executable instructions for creating Bayesian Knowledge Networks (BKNs) for medical conditions, the computer-executable instructions configured for:

• retrieving an audit trail dataset from an Electronic Medical Record (EMR) corresponding to each of a plurality of patients for one or more medical conditions, wherein the audit trail dataset comprises a plurality of events;
• determining a generalized hospital event timeline for each of the one or more medical conditions based on the audit trail dataset, wherein the generalized hospital event timeline comprises a plurality of nodes corresponding to the plurality of events, and wherein the plurality of nodes is connected by unidirected edges in a chronological order of the plurality of events;
• generating a fully connected network of the plurality of nodes of one or more generalized hospital event timelines of the one or more medical conditions, wherein each two of the plurality of nodes in the fully connected network are interconnected via an undirected edge;
• determining a relation type corresponding to each two of the plurality of nodes of the fully connected network based on the one or more generalized hospital event timelines using a causal network learning algorithm;
• and
• creating a BKN from the fully connected network based on the determined relation type for each two of the plurality of nodes.