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PDMS Conference Switzerland Interdisziplinäre Konferenz für Patientendatenmanagementsysteme Workshop Conférence interdisciplinaire pour les systèmes de gestion des données des patients Data Mining and Data Validation • Systemeinführ ung und Nutzung • Datennutzung und Betr iebsstatistik • Diagnosti k und Therapie Partner Kooperationspar tner What is Data Mining? l Progress in digital data acquisition and storage technology has resulted in the growth of huge databases l Interest has grown in the possibility of extracting valuable information from these databases Data mining is the automated analysis of large, observational data sets to find unsuspected relationships and to summarize the data in ways that are both understable and useful to the data owner l The relationships and summaries derived through data mining are often referred to as models or patterns Data Mining Tasks l Description – Find patterns and relations that meaningfully describe the data (e.g. causal relations) l Prediction – Construct a model to foretell values of one variable based on the values of other variables Not always a clear-cut distinction Generalizability is always essential Origins of Data Mining l Draws ideas from machine learning, artificial intelligence, pattern recognition, statistics, and database systems l Eclectic approach: use whatever method is useful Statistics / Pattern recognition Machine Learning / Artificial Intelligence Data Mining Database systems • Clinical Data Mining Dr. Dirk Hüske-Kraus Clinical Director, Clinical Transformation and Education, Philips Patient Care and Clinical Informatics, Böblingen, Germany • Can intracranial hypertension after traumatic brain injury be predicted? Prof. Dr.med. Geert Meyfroidt Intensivist-Anesthesiologist, Associate Professor of Medicine, KU Leuven, Belgium • Discussion