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dc.contributor.authorGrigull, Lorenz
dc.contributor.authorLechner, Werner
dc.contributor.authorPetri, Susanne
dc.contributor.authorKollewe, Katja
dc.contributor.authorDengler, Reinhard
dc.contributor.authorMehmecke, Sandra
dc.contributor.authorSchumacher, Ulrike
dc.contributor.authorLücke, Thomas
dc.contributor.authorSchneider-Gold, Christiane
dc.contributor.authorKöhler, Cornelia
dc.contributor.authorGüttsches, Anne-Katrin
dc.contributor.authorKortum, Xiaowei
dc.contributor.authorKlawonn, Frank
dc.date.accessioned2016-05-18T14:03:13Zen
dc.date.available2016-05-18T14:03:13Zen
dc.date.issued2016en
dc.identifier.citationDiagnostic support for selected neuromuscular diseases using answer-pattern recognition and data mining techniques: a proof of concept multicenter prospective trial. 2016, 16:31 BMC Med Inform Decis Maken
dc.identifier.issn1472-6947en
dc.identifier.pmid26957320en
dc.identifier.doi10.1186/s12911-016-0268-5en
dc.identifier.urihttp://hdl.handle.net/10033/609603en
dc.description.abstractDiagnosis of neuromuscular diseases in primary care is often challenging. Rare diseases such as Pompe disease are easily overlooked by the general practitioner. We therefore aimed to develop a diagnostic support tool using patient-oriented questions and combined data mining algorithms recognizing answer patterns in individuals with selected neuromuscular diseases. A multicenter prospective study for the proof of concept was conducted thereafter.
dc.language.isoenen
dc.titleDiagnostic support for selected neuromuscular diseases using answer-pattern recognition and data mining techniques: a proof of concept multicenter prospective trial.en
dc.typeArticleen
dc.contributor.departmentHelmholtz Centre for infection research, Inhoffenstr. 7, 38124 Braunschweig, Germany.en
dc.identifier.journalBMC medical informatics and decision makingen
refterms.dateFOA2018-06-13T02:36:39Z
html.description.abstractDiagnosis of neuromuscular diseases in primary care is often challenging. Rare diseases such as Pompe disease are easily overlooked by the general practitioner. We therefore aimed to develop a diagnostic support tool using patient-oriented questions and combined data mining algorithms recognizing answer patterns in individuals with selected neuromuscular diseases. A multicenter prospective study for the proof of concept was conducted thereafter.


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