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Predicting the Admission into Medical Studies in Germany: A Data Mining approach. Open Access at KIT

Jung, Dominik; Kemper, Lorenz; Kaempgen, Benedikt; Rettinger, Achim

Abstract:
In Germany, the placement into medical studies programs is highly competitive. Even for excellent applicants success is uncertain. Tackling this uncertainty, the aim of this paper is to investigate the success of an application. Thus applicant data in the time from 2009 to 2012 was analyzed. The characteristics of the statistical patterns lead us to simple recommendations how to alter an application in order to succeed. Our results indicate that Data Mining can outperform personal predictions.


Zugehörige Institution(en) am KIT Institut für Angewandte Informatik und Formale Beschreibungsverfahren (AIFB)
Publikationstyp Forschungsbericht
Jahr 2015
Sprache Englisch
Identifikator DOI(KIT): 10.5445/IR/1000045460
ISSN: 2194-1629
URN: urn:nbn:de:swb:90-454602
KITopen ID: 1000045460
Verlag KIT, Karlsruhe
Umfang XIV S.
Serie KIT Scientific Working Papers ; 27
Schlagworte Predicting Admission; Medical Studies; Data Mining; Knowledge Discovery; Data Exploration
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