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Application of a Medical Text Indexer to an Online Dermatology Atlas.
Clinical dermatology cases are presented as images and semi-structured text describing skin lesions and their relationships to disease. Metadata assignment to such cases is hampered by lack of a standardized dermatology vocabulary and facilitated methods for indexing legacy collections. In this pilot study descriptive clinical text from Dermatlas, a Web-based repository of dermatology cases, was indexed to Medical Subject Heading (MeSH) terms using the U.S. National Library of Medicine's Medical Text Indexer (MTI). The MTI is an automated text processing system that derives ranked lists of MeSH terms to describe the content of medical journal citations using knowledge from the Unified Medical Language System (UMLS) and from MEDLINE. For a representative, random sample of 50 Dermatlas cases, the MTI frequently derived MeSH indexing terms that matched expert-assigned terms for Diagnoses (88%), Lesion Types (72%), and Patient Characteristics (Gender and Age Groups, 62% and 84% respectively). This pilot demonstrates the potential for extending the MTI to automate indexing of clinical case presentations and for using MeSH to describe aspects of clinical dermatology.