Jain N L, Friedman C
Department of Medical Informatics, Columbia University, New York, NY, USA.
Proc AMIA Annu Fall Symp. 1997:829-33.
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.
计算机化临床决策支持需要编码数据，但大多数此类数据因存在于自由文本报告中而无法获取。自然语言处理为编码此类数据提供了一种替代方法。MedLEE是一个自然语言处理系统，常用于对胸部X光片和乳房X光检查报告进行编码。在本文中，我们通过将MedLEE的编码与乳房X光检查中心保存的所有可疑发现日志进行比较，研究MedLEE识别可疑乳腺癌乳房X光检查结果的能力。虽然MedLEE能够识别所有可疑发现，但其粒度水平有所不同，特别是在可疑发现的位置方面。因此，自然语言处理是一种用于编码乳房X光检查报告以检测可疑发现的有用技术。
