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Biomedical subjects

Isabelle Bichindaritz

Publications and source records attributed to Isabelle Bichindaritz.

3 recordsLinked to original sources

Mémoire: A framework for semantic interoperability of case-based reasoning systems in biology and medicine.

OBJECTIVE: Mémoire is a framework for sharing and distributing case bases and case-based reasoning (CBR) systems in biology and medicine. METHODS AND MATERIAL: This paper first introduces the semantic Web approach to build a better Web where search engines, knowledge sources and servers, applications and services can live, work, and learn in cooperation. This semantic approach is particularly well suited for biomedical domains because significant ontologies have been developed there and constitute a sound basis for the standardization effort required for the semantic Web. Case-based reasoning systems in biomedicine have also benefited from these biomedical ontologies and models. RESULTS: This article demonstrates for three such systems how a semantics infused approach in CBR gives better, more accurate results in CBR. From this previous work on a semantic approach in CBR in biomedicine, the Mémoire framework has evolved. CONCLUSION: Mémoire proposes a unified OWL-based representation language for cases and case-based ontologies in biomedicine, where a Web Ontology Language (OWL) is a language to represent ontologies on the Web. Mémoire provides a set of tools for building case-based reasoning systems compliant with its language. Mémoire is extensible and can be adapted to different types of biomedical application domains, tasks, and environments. Mémoire will permit bridging the gap within the multiple case-based reasoning systems dedicated to a single domain, and make available to agents and Web services the case-based competency of the CBR systems adopting its interchange language. The approach could be extended to other application domains of CBR.

Artificial Intelligence↗

Case-based reasoning in the health sciences: What's next?

OBJECTIVES: This paper presents current work in case-based reasoning (CBR) in the health sciences, describes current trends and issues, and projects future directions for work in this field. METHODS AND MATERIAL: It represents the contributions of researchers at two workshops on case-based reasoning in the health sciences. These workshops were held at the Fifth International Conference on Case-Based Reasoning (ICCBR-03) and the Seventh European Conference on Case-Based Reasoning (ECCBR-04). RESULTS: Current research in CBR in the health sciences is marked by its richness. Highlighted trends include work in bioinformatics, support to the elderly and people with disabilities, formalization of CBR in biomedicine, and feature and case mining. CONCLUSION: CBR systems are being better designed to account for the complexity of biomedicine, to integrate into clinical settings and to communicate and interact with diverse systems and methods.

Artificial Intelligence↗