Advances in Case-Based Reasoning

We present adapted inductive methods for learning similarities, parameter weights and diagnostic profiles for case-based reasoning. All of these methods can be refined incrementally by applying different types of background knowledge. Diagnostic profiles are used for extending the conventional CBR to solve cases with multiple faults. The context of our work is to supplement a medical documentation and consultation system by CBR techniques, and we present an evaluation with a real-world case base.

[1]  Joachim Baumeister,et al.  Diagnostic Reasoning with Multilevel Set-Covering Models , 2002 .

[2]  Raymond J. Mooney,et al.  Inductive Learning For Abductive Diagnosis , 1994, AAAI.

[3]  Ron Kohavi,et al.  Supervised and Unsupervised Discretization of Continuous Features , 1995, ICML.

[4]  Frank Puppe,et al.  Incremental Development of Diagnostic Set-Covering Models with Therapy Effects , 2003, Int. J. Uncertain. Fuzziness Knowl. Based Syst..

[5]  Agnar Aamodt,et al.  Case-Based Reasoning: Foundational Issues, Methodological Variations, and System Approaches , 1994, AI Commun..

[6]  Christoph Beierle,et al.  Methoden wissensbasierter Systeme - Grundlagen, Algorithmen, Anwendungen , 2000, International Conference on Climate Informatics.

[7]  David L. Waltz,et al.  Toward memory-based reasoning , 1986, CACM.

[8]  Tony R. Martinez,et al.  Improved Heterogeneous Distance Functions , 1996, J. Artif. Intell. Res..

[9]  Rainer Schmidt,et al.  Case-Based Reasoning for Antibiotics Therapy Advice , 1999, ICCBR.

[10]  Jiawei Han,et al.  Data Mining: Concepts and Techniques , 2000 .

[11]  Frank Puppe,et al.  HepatoConsult: a knowledge-based second opinion and documentation system , 2002, Artif. Intell. Medicine.

[12]  Frank Puppe Knowledge reuse among diagnostic problem-solving methods in the Shell-Kit D3 , 1998, Int. J. Hum. Comput. Stud..

[13]  Judea Pearl,et al.  Probabilistic reasoning in intelligent systems - networks of plausible inference , 1991, Morgan Kaufmann series in representation and reasoning.

[14]  Tony R. Martinez,et al.  An Empirical Comparison of Discretization Methods , 1995 .

[15]  C. McGreavy,et al.  Learning dynamic fault models based on a fuzzy set covering method , 1997 .

[16]  Phyllis Koton,et al.  Reasoning about Evidence in Causal Explanations , 1988, AAAI.

[17]  Michael M. Richter,et al.  The Knowledge Contained in Similarity Measures , 1995 .

[18]  Luigi Portinale,et al.  ADAPtER: An Integrated Diagnostic System Combining Case-Based and Abductive Reasoning , 1995, ICCBR.

[19]  David W. Aha,et al.  Weighting Features , 1995, ICCBR.