Combining voice recognition and automatic indexing of medical reports
Medical records have been evolving from the traditional paper-based records to digital ones, from the method of dictating reports and transcription to voice recognition systems. The transition to digital operations will not be complete until we have the ability to combine voice recognition with automatic indexing of texts. This paper introduces the methods we used to evaluate existing voice recognition software programs and presents NOMINDEX, a system that turns a medical text into MeSH codes, using the French ADM lexical database. Those systems were applied to 28 patient discharge summaries in French, produced after a coronarography, and extracted from the MENELAS corpus of texts. Using the best configuration for voice recognition, the rate of accurate recognition exceeds 98 per cent. Among the indexing concepts assigned by NOMINDEX, 25 per cent were not pertinent and 12 per cent of the relevant concepts were missing. Most errors were related to confusion between common language and medical language, and to the coverage of the ADM lexical database. Best results would be expected with a more comprehensive lexical resource. In addition, only 3 per cent of the errors generated by inadequate voice recognition that remained in the configuration that performed better, impacted on automatic indexing by NOMINDEX.
Bibliographic Reference: An oral report given at: MIE2002, XVIIth International Congress of the European Federation for Medical Informatics Organised by: European Federation for Medical Informatics (EFMI) Held at: Budapest (HU), 25-29 August 2002
Record Number: 200214521 / Last updated on: 2002-04-03
Original language: en
Available languages: en