Article (APB:09)
Atzmueller, M.; Puppe, F. & Buscher, H.-P.
A Semi-Automatic Approach for Confounding-Aware Subgroup Discovery
International Journal on Artificial Intelligence Tools (IJAIT), 2009, 18, 1 - 18

Inproceedings (AN:09a)
Atzmueller, M. & Nalepa, G. J.
A Textual Subgroup Mining Approach for Rapid ARD+ Model Capture
2009

Article (AN:09b)
Atzmueller, M. & Nalepa, G. J.
Towards Rapid Knowledge Capture using Textual Subgroup Mining for Rule Prototyping
Technical Report 458, Institute of Computer Science, University of Würzburg, 2009

Inproceedings (AS:08b)
Atzmueller, M. & Seipel, D.
Causal Subgroup Analysis for Detecting Confounding (Extended version)
2008

Inproceedings (AS:08a)
Atzmueller, M. & Seipel, D.
Declarative Specification of Ontological Domain Knowledge for Descriptive Data Mining (Extended version)
2008

Inproceedings (ABHMLP:08)
Atzmueller, M.; Beer, S.; Hörnlein, A.; Melcher, R.; Lührs, H. & Puppe, F.
Design and Implementation of a Data Warehouse for Quality Management, System Evaluation and Knowledge Discovery in the Medical Domain
2008

Book (BA:08)
Baumeister, J. & Atzmueller, M. (ed.)
Proceedings of the LWA 2008 - Lernen, Wissen, Adaptivität
Institute of Computer Science, University of Würzburg, 2008

Book (Atzmueller:07)
Atzmueller, M.
Knowledge-Intensive Subgroup Mining -- Techniques for Automatic and Interactive Discovery
IOS Press, 2007, 307

Article (ABP:05Score)
Atzmueller, M.; Baumeister, J. & Puppe, F.
Semi-Automatic Learning of Simple Diagnostic Scores Utilizing Complexity Measures
Artificial Intelligence in Medicine. Special Issue on Intelligent Data Analysis in Medicine, 2006, 37, 19-30

Inproceedings (ABP:05)
Atzmueller, M.; Baumeister, J. & Puppe, F.
Exemplifying Subgroup Mining Results for Interactive Knowledge Refinement
2005, 101-106

Inproceedings (APB:05a)
Atzmueller, M.; Puppe, F. & Buscher, H.-P.
Exploiting Background Knowledge for Knowledge-Intensive Subgroup Discovery
2005, 647-652

Inproceedings (APB:05b)
Atzmueller, M.; Puppe, F. & Buscher, H.-P.
Profiling Examiners using Intelligent Subgroup Mining
2005, 46-51

Inproceedings (ABHRP:05)
Atzmueller, M.; Baumeister, J.; Hemsing, A.; Richter, E.-J. & Puppe, F.
Subgroup Mining for Interactive Knowledge Refinement
2005, 453-462

Inproceedings (PBAHB:05)
Puppe, F.; Buscher, G.; Atzmueller, M.; Huettig, M. & Buscher, H.-P.
Clinical Experiences with a Knowledge-Based System in Sonography (SonoConsult)
2005, 319–-329

Inproceedings (ASBPB:04)
Atzmueller, M.; Shi, W.; Baumeister, J.; Puppe, F. & Barnden, J. A.
Barr, V. & Markov, Z. (ed.)
Case-Based Approaches for Diagnosing Multiple Disorders
AAAI Press, 2004, 154-159

Inproceedings (ABP:04)
Atzmueller, M.; Baumeister, J. & Puppe, F.
Quality Measures for Semi-Automatic Learning of Simple Diagnostic Rule Bases
2004, 203-213

Inproceedings (APB:04)
Atzmueller, M.; Puppe, F. & Buscher, H.-P.
Towards Knowledge-Intensive Subgroup Discovery
2004, 117-123

Inproceedings (ABP:03)
Atzmueller, M.; Baumeister, J. & Puppe, F.
Evaluation of two Strategies for Case-Based Diagnosis handling Multiple Faults
2003

Inproceedings (ABP:03Score)
Atzmueller, M.; Baumeister, J. & Puppe, F.
Inductive Learning of Simple Diagnostic Scores
2003, 23-30

Inproceedings (BAP:02)
Baumeister, J.; Atzmueller, M. & Puppe, F.
Inductive Learning for Case-Based Diagnosis with Multiple Faults
2002, 2416, 28-42