Systems, methods, and articles for imputing directed temporal measurements

A computing system for imputing a value associated with a subject within a structured electronic health record (EHR) system, the computing system comprising:

• one or more processors;
• and
• one or more non-transitory computer-readable media collectively storing instructions that, when collectively executed by the one or more processors, cause the one or more processors to perform actions, the actions comprising:
• receiving a request to impute the value associated with the subject at a temporal instance;
• retrieving a subset of data associated with the subject from the EHR system, the subset of data comprising a plurality of stored values associated with one or more temporal instances;
• providing the temporal instance indicated in the request and the subset of data to a trained artificial intelligence engine, the trained artificial intelligence engine configured to perform actions, comprising:
• determining relationships between the stored values, the relationships being determined by calculating a set of scores for multiple subsets of features of the stored values that represent interdependencies between the stored values;
• adjusting the calculated scores based on a temporal proximity of the one or more temporal instances of the stored values relative to the temporal instance of the value being imputed to generate time-adjusted scores;
• and
• generating an imputed value by creating a weighted combination of the stored values, wherein the weights are determined based on the time-adjusted scores for the multiple subsets of features of the stored values;
• and
• providing the imputed value in response to the request.

One or more non-transitory computer readable media collectively storing a computer program thereon, the program, when collectively executed by one or more processors, implements operations for imputing a value associated with a subject within a structured electronic health record (EHR) system, the operations comprising:

• receiving a request to impute the value associated with the subject at a temporal instance;
• retrieving a subset of data associated with the subject from the EHR system, the subset of data comprising a plurality of stored values associated with one or more temporal instances;
• providing the temporal instance indicated in the request and the subset of data to a trained artificial intelligence engine, the trained artificial intelligence engine configured to perform actions, comprising:
• determining relationships between the stored values, the relationships being determined by calculating a set of scores for multiple subsets of features of the stored values that represent interdependencies between the stored values;
• adjusting the calculated scores based on a temporal proximity of the one or more temporal instances of the stored values relative to the temporal instance of the value being imputed to generate time-adjusted scores;
• and
• generating an imputed value by creating a weighted combination of the stored values, wherein the weights are determined based on the time-adjusted scores for the multiple subsets of features of the stored values;
• and
• providing the imputed value in response to the request.