Selective automated indexing of findings and diagnoses in radiology reports.
The recent improvements in capabilities of desktop computers and communications networks give impetus for the development of clinical image repositories that can be used for patient care and medical education. A challenge in the use of these systems is the accurate indexing of images for retrieval performance acceptable to users. This paper describes a series of experiments aiming to adapt the SAPHIRE system, which matches text to concepts in the UMLS Metathesaurus, for the automated indexing of image reports. A series of enhancements to the baseline system resulted in a recall of 63% but a precision of only 30% in detecting concepts. At this level of performance, such a system might be problematic for users in a purely automated indexing environment. However, if the ability to retrieve images in repositories based on content in their reports is desired by clinical users, and no other current systems offer this functionality, then follow-up research questions include whether these imperfect results would be useful in a completely or partially automated indexing environment and/or whether other approaches can improve upon them.
Hersh
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W
Division of Medical Informatics and Outcomes Research, Oregon Health and Science University, Portland, Oregon 97201, USA. hersh@ohsu.edu
Mailhot
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Arnott-Smith
C
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Lowe
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H
D000043:Abstracting and Indexing; D000465:Algorithms; D019295:Computational Biology; D003199:Computer Systems; D006801:Humans; D009323:Natural Language Processing; D011873:Radiology Information Systems; D017432:Unified Medical Language System