This paper describes the application of an ensemble of indexing and classification systems, which have been shown to be successful in information retrieval and classification of medical literature, to a new task of assigning ICD-9-CM codes to the clinical history and impression sections of radiology reports. The basic methods used are: a modification of the NLM Medical Text Indexer system, SVM, k-NN and a simple pattern-matching method. The basic methods are combined using a variant of stacking. Evaluated in the context of a Medical NLP Challenge, fusion produced an Fscore of 0.85 on the Challenge test set, which is considerably above the mean Challenge F-score of 0.77 for 44 participating groups.
codes to radiology reports REF .
From indexing the biomedical literature to coding clinical text: experience with MTI and machine learning approaches
Biological, translational, and clinical language processing
Computer Science