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

Atzmueller, M. & Nalepa, G. J. (2009). A Textual Subgroup Mining Approach for Rapid ARD+ Model Capture. Proc. 22nd International Florida Artificial Intelligence Research Society Conference (FLAIRS), accepted,.
, M. & Nalepa, G. J. (2009). Towards Rapid Knowledge Capture using Textual Subgroup Mining for Rule Prototyping. Technical Report 458, Institute of Computer Science, University of Würzburg, . 

Atzmueller, M. & Puppe, F. (2008). A Case-Based Approach for Characterization and Analysis of Subgroup Patterns. Journal of Applied Intelligence, 28, 210-221. 

Atzmueller, M. & Seipel, D. (2008). Causal Subgroup Analysis for Detecting Confounding (Extended version). Proc. 18th International Conference on Applications of Declarative Programming and Knowledge Management, accepted,.

Atzmueller, M. & Seipel, D. (2008). Declarative Specification of Ontological Domain Knowledge for Descriptive Data Mining (Extended version). Proc. 18th International Conference on Applications of Declarative Programming and Knowledge Management, accepted,.

Atzmueller, M., Beer, S., Hцrnlein, A., Melcher, R., Lührs, H. & Puppe, F. (2008). Design and Implementation of a Data Warehouse for Quality Management, System Evaluation and Knowledge Discovery in the Medical Domain. Proc. 1st European Workshop on Design, Evaluation and Refinement of Intelligent Systems,.

 & Baumeister, J. & Atzmueller, M. (eds.) (2008).Proceedings of the LWA 2008 - Lernen, Wissen, Adaptivitдt. Institute of Computer Science, University of Würzburg.

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

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

Atzmueller, M., Puppe, F. & Buscher, H.-P. (2005). Exploiting Background Knowledge for Knowledge-Intensive Subgroup Discovery. Proc. 19th International Joint Conference on Artificial Intelligence (IJCAI-05) (p./pp. 647--652),.

Atzmueller, M., Puppe, F. & Buscher, H.-P. (2005). Profiling Examiners using Intelligent Subgroup Mining. Proc. 10th International Workshop on Intelligent Data Analysis in Medicine and Pharmacology (IDAMAP-2005) (p./pp. 46--51),.

Atzmueller, M., Baumeister, J., Hemsing, A., Richter, E.-J. & Puppe, F. (2005). Subgroup Mining for Interactive Knowledge Refinement. Proc. 10th Conference on Artificial Intelligence in Medicine (AIME 05) (p./pp. 453--462),.

Puppe, F., Buscher, G., Atzmueller, M., Huettig, M. & Buscher, H.-P. (2005). Clinical Experiences with a Knowledge-Based System in Sonography (SonoConsult). Professional Knowledge Management (p./pp. 319вЂ“-329),.

Atzmueller, M., Shi, W., Baumeister, J., Puppe, F. & Barnden, J. A. (2004). Case-Based Approaches for Diagnosing Multiple Disorders. In V. Barr & Z. Markov (eds.), Proc. 17th Intl. Florida Artificial Intelligence Research Society Conference 2004 (FLAIRS-2004) (p./pp. 154--159),: AAAI Press.

Atzmueller, M., Baumeister, J. & Puppe, F. (2004). Quality Measures for Semi-Automatic Learning of Simple Diagnostic Rule Bases. Proc. 15th Intl. Conference on Applications of Declarative Programming and Knowledge Management (INAP 2004) (p./pp. 203--213),.

Atzmueller, M., Puppe, F. & Buscher, H.-P. (2004). Towards Knowledge-Intensive Subgroup Discovery. Proc. LWA 2004 Workshop, Germany (p./pp. 117--123),.

Atzmueller, M., Baumeister, J. & Puppe, F. (2003). Evaluation of two Strategies for Case-Based Diagnosis handling Multiple Faults. Proc. 2nd Conf. Professional Knowledge Management (WM2003),.

Atzmueller, M., Baumeister, J. & Puppe, F. (2003). Inductive Learning of Simple Diagnostic Scores. Medical Data Analysis, Proc. 4th Intl. Symposium on Medical Data Analysis (ISMDA 2003), LNCS 2868 (p./pp. 23-30),.

Baumeister, J., Atzmueller, M. & Puppe, F. (2002). Inductive Learning for Case-Based Diagnosis with Multiple Faults. Advances in Case-Based Reasoning (p./pp. 28-42),.