Stephan Dreiseitl
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Logistic regression and artificial neural network classification models: a methodology review
S Dreiseitl, L Ohno-Machado
Journal of biomedical informatics 35 (5-6), 352-359, 2002
A comparison of machine learning methods for the diagnosis of pigmented skin lesions
S Dreiseitl, L Ohno-Machado, H Kittler, S Vinterbo, H Billhardt, M Binder
Journal of biomedical informatics 34 (1), 28-36, 2001
Comparing three-class diagnostic tests by three-way ROC analysis
S Dreiseitl, L Ohno-Machado, M Binder
Medical Decision Making 20 (3), 323-331, 2000
The CHOP postnatal weight gain, birth weight, and gestational age retinopathy of prematurity risk model
G Binenbaum, G Ying, GE Quinn, J Huang, S Dreiseitl, J Antigua, ...
Archives of Ophthalmology 130 (12), 1560-1565, 2012
A clinical prediction model to stratify retinopathy of prematurity risk using postnatal weight gain
G Binenbaum, G Ying, GE Quinn, S Dreiseitl, K Karp, RS Roberts, ...
Pediatrics 127 (3), e607-e614, 2011
Do physicians value decision support? A look at the effect of decision support systems on physician opinion
S Dreiseitl, M Binder
Artificial intelligence in medicine 33 (1), 25-30, 2005
Computer-aided epiluminescence microscopy of pigmented skin lesions: the value of clinical data for the classification process
M Binder, H Kittler, S Dreiseitl, H Ganster, K Wolff, H Pehamberger
Melanoma research 10 (6), 556-561, 2000
A new rule-based algorithm for identifying metabolic markers in prostate cancer using tandem mass spectrometry
M Osl, S Dreiseitl, B Pfeifer, K Weinberger, H Klocker, G Bartsch, ...
Bioinformatics 24 (24), 2908-2914, 2008
Computer versus human diagnosis of melanoma: evaluation of the feasibility of an automated diagnostic system in a prospective clinical trial
S Dreiseitl, M Binder, K Hable, H Kittler
Melanoma research 19 (3), 180-184, 2009
Outlier detection with one-class SVMs: an application to melanoma prognosis
S Dreiseitl, M Osl, C Scheibböck, M Binder
AMIA annual symposium proceedings 2010, 172, 2010
Risk stratification in heart failure using artificial neural networks.
F Atienza, N Martinez-Alzamora, JA De Velasco, S Dreiseitl, ...
Proceedings of the AMIA Symposium, 32, 2000
Using concept hierarchies to improve calculation of patient similarity
D Girardi, S Wartner, G Halmerbauer, M Ehrenmüller, H Kosorus, ...
Journal of biomedical informatics 63, 66-73, 2016
A prospective study of mobile phones for dermatology in a clinical setting
J Weingast, C Scheibböck, EMT Wurm, E Ranharter, S Porkert, S Dreiseitl, ...
Journal of telemedicine and telecare 19 (4), 213-218, 2013
Evaluating variable selection methods for diagnosis of myocardial infarction.
S Dreiseitl, L Ohno-Machado, S Vinterbo
Proceedings of the AMIA Symposium, 246, 1999
Differences in examination characteristics of pigmented skin lesions: Results of an eye tracking study
S Dreiseitl, M Pivec, M Binder
Artificial intelligence in medicine 54 (3), 201-205, 2012
Demoting redundant features to improve the discriminatory ability in cancer data
M Osl, S Dreiseitl, F Cerqueira, M Netzer, B Pfeifer, C Baumgartner
Journal of biomedical informatics 42 (4), 721-725, 2009
Effects of data anonymization by cell suppression on descriptive statistics and predictive modeling performance
L Ohno-Machado, S Vinterbo, S Dreiseitl
Journal of the American Medical Informatics Association 9 (Supplement_6 …, 2002
Disambiguation data: extracting information from anonymized sources
S Dreiseitl, S Vinterbo, L Ohno-Machado
Journal of the American Medical Informatics Association 9 (Supplement_6 …, 2002
Analysis of heart rate variability (HRV) feature robustness for measuring technostress
D Baumgartner, T Fischer, R Riedl, S Dreiseitl
Information systems and neuroscience: NeuroIS retreat 2018, 221-228, 2019
Applying a decision support system in clinical practice: results from melanoma diagnosis
S Dreiseitl, M Binder, S Vinterbo, H Kittler
AMIA Annual Symposium Proceedings 2007, 191, 2007
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