International Business Machines Corporation

Hyuna Yang

Yajuan Wang

Gigi Y C Yuen-Reed

Gigi Yuen-Reed

Kathryn L Howard

A method, a computing system and a computer program product are provided. A model is generated and trained. The model is based on clinical data with outcomes from clinically-defined hierarchical metadata in a selected level of clinically-defined hierarchical metadata serving as an initial set of prediction targets. A score is determined for each of the prediction targets based on the generated model and the set of evaluation factors. The set of prediction targets, the generated model, and the scores for the set of prediction targets are updated until the updated scores for the updated set of prediction targets satisfy acceptance criteria. The updated generated model, using the updated set of prediction targets, is applied to predict one of a set of updated prediction targets of mutually exclusive outcome categories.

Constructing prediction targets from a clinically-defined hierarchy

Embodiments of the present invention disclose a method, a computer program product, and a computer system for enriching data. A computer receives a limited dataset and a target insight. In addition, the computer identifies an applicable richer dataset and determines a population relatedness between the limited dataset and the applicable richer dataset. Moreover, the computer calculates estimators of features using the richer dataset as well as calculates estimators for features using the limited dataset. The computer then updates the estimators of the limited dataset using estimators of the richer dataset and evaluates the updated estimators. Lastly, the computer provides a data collection recommendation as it relates to the limited dataset based on the evaluation.

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Somerville, MA, United States of America

Hyuna Yang