Abstract: This disclosure describes systems, devices, and techniques for identifying sections of medical documents that are suitable for automated medical coding. In one example, a computer-implemented method includes receiving, by one or more processors, the medical document, wherein the medical document comprises a plurality of sections. The method also may include determining, by the one or more processors and via application of a classification model to each section of the plurality of sections, codability indicia for each section of the plurality of sections, wherein the codability indicia represents whether the respective section is suitable for automated medical coding. The method may include outputting, by the one or more processors, the respective codability indicia for each section of the plurality of sections.

Abstract: This disclosure describes a computerized system for managing medical information, the system including at least one computing device configured to receive a plurality of medical documents, determine skip grams comprising tokens for the plurality of medical documents, wherein each of the skip grams comprises one or more tokens of at least one of the medical documents, and populate a trie data structure based on the skip grams. The at least one computing device is further configured to prune the plurality of nodes of the trie based on one or more criteria to produce a pruned trie of nodes, determine rules for associating medical billing codes with the skip grams of the pruned trie of nodes based on pointwise mutual information, and output the determined rules.

Abstract: This disclosure describes systems, devices, and techniques for identifying sections of medical documents that are suitable for automated medical coding. In one example, a computer-implemented method includes receiving, by one or more processors, the medical document, wherein the medical document comprises a plurality of sections. The method also may include determining, by the one or more processors and via application of a classification model to each section of the plurality of sections, codability indicia for each section of the plurality of sections, wherein the codability indicia represents whether the respective section is suitable for automated medical coding. The method may include outputting, by the one or more processors, the respective codability indicia for each section of the plurality of sections.

Abstract: This disclosure describes a computerized system for managing medical information, the system including at least one computing device configured to receive a plurality of medical documents, determine skip grams comprising tokens for the plurality of medical documents, wherein each of the skip grams comprises one or more tokens of at least one of the medical documents, and populate a trie data structure based on the skip grams. The at least one computing device is further configured to prune the plurality of nodes of the trie based on one or more criteria to produce a pruned trie of nodes, determine rules for associating medical billing codes with the skip grams of the pruned trie of nodes based on pointwise mutual information, and output the determined rules.