Work

Automatic identification of pneumonia related concepts on chest x-ray reports.

Year: 1999

Type: article

Abstract: A medical language processing system called SymText, two other automated methods, and a lay person were compared against an internal medicine resident for their ability to identify pneumonia related concepts on chest x-ray reports. Sensitivity (recall), specificity, and positive predictive value (precision) are reported with respect to an independent panel of physicians. Overall the performance of SymText was similar to the physician and superior to the other methods. The automatic encoding of pneumonia concepts will support clinical research, decision making, computerized clinical protocols, and quality assurance in a radiology department.

Source: PubMed Central

Authors: M Fiszman, W W Chapman, S R Evans, P J Haug

Institutions: University of Utah, LDS Hospital

Language: English

Topic: Biomedical Text Mining and Ontologies

Subfield: Health Informatics

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: green

Funders: National Heart, Lung, and Blood Institute, U.S. National Library of Medicine

Awards: QUALITY ASSURANCE SYSTEM FOR RADIOLOGY REPORTING, SEMANTIC PARSER FOR MEDICAL FREE TEXT