Abstract
Case-based reasoning (CBR) is an Artificial Intelligence (AI) approach with broad applicability to building intelligent systems in health sciences domains. It represents knowledge in the form of exemplary past experiences, or cases. It is especially well suited to health sciences domains, where experience plays a major role in acquiring knowledge and skill, and where case histories inform current practice. This chapter provides a broad overview of CBR in the Health Sciences, including its foundations and research directions. It begins with introductions to the CBR approach and to health sciences domains, and then explains their synergistic combination. It continues with a discussion of the relationship between CBR and statistical data analysis, and shows how CBR supports evidence-based practice. Next, it presents an in-depth analysis of current work in the field, classifying CBR in the Health Sciences systems in terms of their domains, purposes, memory and case management, reasoning, and system design. Finally, it places CBR with respect to other AI approaches used in health sciences domains, showing how CBR can complement these approaches in multimodal reasoning systems.
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