Systems, Methods, and Devices for Automatically Converting Explanation of Benefits (EOB) Printable Documents into Electronic Format using Artificial Intelligence Techniques

Tangible, non-transitory computer-readable media comprising program instructions stored therein, wherein the program instructions, when executed by one or more processors, cause a computing system to perform functions comprising:

• receiving a plurality of images of documents;
• for each received image, using an image classification algorithm to classify the image as one of (i) an image of a first type of document from one of a plurality of sources, or (ii) an image of a second type of document;
• for each image classified as an image of the first type of document from one of the plurality of sources, using an object localization algorithm to identity an area of interest in the image;
• for an identified area of interest, using an optical character recognition algorithm to extract text from the identified area of interest;
• and
• populating a record associated with the document with the extracted text.

A method performed by a computing system, the method comprising:

• receiving a plurality of images of documents;
• for each received image, using an image classification algorithm to classify the image as one of an image of an Explanation of Benefits (EOB) document from one of a plurality of payers or an image of a document other than an EOB document, wherein using the image classification algorithm to classify the image as one of an image of an Explanation of Benefits (EOB) document from one of a plurality of payers or an image of a document other than an EOB document comprises (i) using an autoencoder to generate a feature vector corresponding to the image, (ii) determining a plurality of similarity scores for the image, wherein each similarity score corresponds to a similarity between (a) the feature vector corresponding to the image and (b) a representative feature vector corresponding to one of the plurality of payers, and (iii) classifying the image as corresponding to an EOB document from one of the plurality of payers based at least in part on the plurality of determined similarly scores, wherein classifying the image as corresponding to an EOB document from one of the plurality of payers based at least in part on the plurality of determined similarly scores comprises (a) generating a first classification of the image, wherein the first classification identifies one of the plurality of payers, (b) when the one of the plurality of payers identified in the first classification is consistent with payer information within EDI-837 data corresponding to the image, selecting the first classification as the classification of the image, and (c) when the one of the plurality of payers identified in the first classification is inconsistent with payer information within EDI-837 data corresponding to the image, generating a second classification of the image, wherein the second classification identifies one of the plurality of payers that is different than the payer identified in the first classification;
• for each image classified as an image of an Explanation of Benefits (EOB) document from one of the plurality of payers, using an object localization algorithm to identity an area of interest in the image;
• for an identified area of interest, using an optical character recognition algorithm to extract text from the identified area of interest;
• and
• populating a record associated with the Explanation of Benefits (EOB) document from one of the plurality of payers with the extracted text.