Abstract: Embodiments of present disclosure provide a system, apparatus and method(s) for generating a set of metrics for evaluating entities used with a predictive machine learning model, the method comprising: selecting one or more sets of entities from a data sources for generating a plurality of predictions aggregated from said one or more sets of entities using one or more pre-trained predictive models; selecting a subset of predictions from the plurality of predictions based on said one or more sets of entities in relation to the data source; extracting metadata from the data source associated with the subset of predictions, where the metadata comprises entity metadata and predicted metadata; generating the set of metrics based on the metadata extracted and the subset of predictions; and outputting the set of metrics for evaluation.

Abstract: A computer-implemented method of electronically mining medical and scientific datasets to determine a ranking indicating a level of evidence for an association between two entities is disclosed. The method comprises receiving a representation of an entity pair, performing first data mining on one or more unstructured datasets to generate one or more first scores each representing an extent of association between the entities of the entity pair, and performing second data mining on one or more structured datasets to generate one or more second scores each representing an extent of association between the entities of the entity pair. The method also comprises using a classifier to determine a predicted ranking for the entity pair using the one or more first scores and the one or more second scores, and providing the predicted ranking to a user as an indication of the strength of evidence for an association between the entities of the entity pair.