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A Framework for Expert-Driven Subpopulation Discovery and Evaluation Using Subspace Clustering for Epidemiological Data. Expert Systems with Applications, (113):147 - 160, 2018. URL
Building a Bayesian Network to Understand the Interplay of Variables in an Epidemiological Population-Based Study. Proc. of the 31th IEEE Int. Symposium on Computer-Based Medical Systems (CBMS18), 88-93, 2018.
Rupture Status Classification of Intracranial Aneurysms Using Morphological Parameters. Proc. of the 31th IEEE Int. Symposium on Computer-Based Medical Systems (CBMS18), 48-53, 2018.
Transformation of Temperature Timeseries into Features that Characterize Patients with Diabetic Autonomic Nerve Disorder. Proc. of the 31th IEEE Int. Symposium on Computer-Based Medical Systems (CBMS18), 65-70, 2018.
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Visual Analytics of Missing Data in Epidemiological Cohort Studies. Eurographics Workshop on Visual Computing for Biology and Medicine (VCBM), 43-52, 2017.
Classification of DCE-MRI Data for Breast Cancer Diagnosis Combining Contrast Agent Dynamics and Texture Features. Bildverarbeitung für die Medizin (BVM), 325-330, Springer Verlag, Heidelberg, 2017.
Combining Subgroup Discovery and Clustering to Identify Diverse Subpopulations in Cohort Study Data. Proc. of the 30th IEEE Int. Symposium on Computer-Based Medical Systems (CBMS17), 582-587, 2017.
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Learning Pressure Patterns for Patients with Diabetic Foot Syndrome. Proc. of the 29th IEEE Int. Symposium on Computer-Based Medical Systems (CBMS16), IEEE, Dublin, Ireland and Belfast, Northern Ireland, June 2016.
Comparative Clustering of Plantar Pressure Distributions in Diabetics with Polyneuropathy May Be Applied to Reveal Inappropriate Biomechanical Stress. PLoS ONE, (11)8:1-12, Public Library of Science, August 2016. URL
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Can we classify the participants of a longitudinal epidemiological study from their previous evolution?. Proc. of the 28th IEEE Int. Symposium on Computer-Based Medical Systems (CBMS15), 121-126, IEEE, São Carlos and Ribeirão Preto, Brazil, June 2015. URL
Learning and inspecting classification rules from longitudinal epidemiological data to identify predictive features on hepatic steatosis. Expert Systems with Applications, (41)11:5405-5415, Elsevier BV, September 2014. URL
Subpopulation Discovery in Epidemiological Data with Subspace Clustering. Foundations of Computing and Decision Sciences (FCDS), (39)4:271-300, 2014. URL
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Classification of Benign and Malignant DCE-MRI Breast Tumors by Analyzing the Most Suspect Region. In Hans-Peter Meinzer, Thomas Martin Deserno, Heinz Handels, and Thomas Tolxdorff (Eds.), Bildverarbeitung für die Medizin 2013, 45-50, Springer Berlin Heidelberg, 2013. URL
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