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Proceedings of the AMIA Annual Fall Symposium logoLink to Proceedings of the AMIA Annual Fall Symposium
. 1997:829–833.

Identification of findings suspicious for breast cancer based on natural language processing of mammogram reports.

N L Jain 1, C Friedman 1
PMCID: PMC2233320  PMID: 9357741

Abstract

There is need for encoded data for computerized clinical decision support, but most such data are unavailable as they are in free-text reports. Natural language processing offers one alternative for encoding such data. MedLEE is a natural language processing system which is in routine use for encoding chest radiograph and mammogram reports. In this paper, we study MedLEE's ability to identify mammogram findings suspicious for breast cancer by comparing MedLEE's encoding with a logbook of all suspicious findings maintained by the mammography center. While MedLEE was able to identify all the suspicious findings, it varied in the level of granularity, particularly about the location of the suspicious finding. Thus, natural language processing is a useful technique for encoding mammogram reports in order to detect suspicious findings.

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Selected References

These references are in PubMed. This may not be the complete list of references from this article.

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