Using natural language processing to extract mammographic findings.

ABSTRACT:

Objective

Structured data on mammographic findings are difficult to obtain without manual review. We developed and evaluated a rule-based natural language processing (NLP) system to extract mammographic findings from free-text mammography reports.

Materials and methods

The NLP system extracted four mammographic findings: mass, calcification, asymmetry, and architectural distortion, using a dictionary look-up method on 93,705 mammography reports from Group Health. Status annotations and anatomical location annotation were associated to each NLP detected finding through association rules. After excluding negated, uncertain, and historical findings, affirmative mentions of detected findings were summarized. Confidence flags were developed to denote reports with highly confident

SUBMITTER: Gao H 

PROVIDER: S-EPMC4408241 | biostudies-literature | 2015 Apr

REPOSITORIES: biostudies-literature