André Happe

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OBJECTIVE The objective of this project is to investigate methods whereby a combination of speech recognition and automated indexing methods substitute for current transcription and indexing practices. METHODS We based our study on existing speech recognition software programs and on NOMINDEX, a tool that extracts MeSH concepts from medical text in(More)
High amount of relevant information is contained in reports stored in the electronic patient records and associated metadata. R-oogle is a project aiming at developing information retrieval engines adapted to these reports and designed for clinicians. The system consists in a data warehouse (full-text reports and structured data) imported from two different(More)
To compare serious adverse events of fixed-dose dual antihypertensive drug combination (FIXED) to component-based free-combination (FREE).A population-based nationwide cohort from the French Health Insurance System included subjects over 50 years with first time claims (new user) in the second half of 2009 for a calcium-channel blocker or a thiazide-like(More)
An algorithm for automatic coding of pathology reports using a multi-axial codification (ADICAP) is described and evaluated. It extracts << significant words >> or expressions from a corpus and records the statistical relationships between them and the modalities of the different axes. Different weighting functions are evaluated. With the best settings, in(More)
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 automated indexing of texts. This paper introduces the methods(More)
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