| CPC G06N 5/045 (2013.01) [G06F 18/214 (2023.01); G06N 20/20 (2019.01); G06Q 10/10 (2013.01)] | 27 Claims |
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1. A method for predicting performance of a provider comprising:
receiving data associated with a claim involving the provider;
inputting the data associated with the claim into a supervised machine learning model and receiving a predicted performance of the claim as output, wherein the supervised machine learning model has been trained on structured data and unstructured data;
selecting a first unsupervised machine learning model from a plurality of unsupervised machine learning models by determining whether information available for the claim satisfies data fields associated with a stage in claim processing that the claim belongs to, one or more of the plurality of unsupervised machine learning models associated with a different stage of a plurality of stages in claim processing, wherein the plurality of stages comprise information associated with the claim as the claim progresses;
inputting the data associated with the claim into the selected first unsupervised machine learning model and receiving as output from the selected first unsupervised machine learning model an identification of a cluster of candidate claims to which the claim belongs;
generating a score corresponding to a predicted performance of the provider based on the predicted performance of the claim and the identification of the cluster of candidate claims; and
providing, for display at a client device, the generated score of the provider.
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