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Synergistic case-based reasoning in medical domains
Ohio University, Athens, OH 45701, USA.
Università del Piemonte Orientale.
State University of New York at Oswego.
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems. (IS (Embedded Systems))ORCID iD: 0000-0002-5562-1424
2014 (English)In: Expert systems with applications, ISSN 0957-4174, E-ISSN 1873-6793, Vol. 41, no 2, p. 249-259Article in journal (Refereed) Published
Abstract [en]

This paper presents four synergistic systems that exemplify the approaches and benefits of case-based reasoning in medical domains. It then explores how these systems couple Artificial Intelligence (AI) research with medical research and practice, integrate multiple AI and computing methodologies, leverage small numbers of available cases, reason with time series data, and integrate numeric data with contextual and subjective information. The following systems are presented: (1) CARE-PARTNER, which supports the long-term follow-up care of stem-cell transplantation patients; (2) the 4 Diabetes Support System, which aids in managing patients with type 1 diabetes on insulin pump therapy; (3) Retrieval of HEmodialysis in NEphrological Disorders, which supports hemodialysis treatment of patients with end stage renal disease; and (4) the Mälardalen Stress System, which aids in the diagnosis and treatment of stress-related disorders.

Place, publisher, year, edition, pages
2014. Vol. 41, no 2, p. 249-259
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:mdh:diva-21410DOI: 10.1016/j.eswa.2013.05.063ISI: 000327279900002Scopus ID: 2-s2.0-84885960318OAI: oai:DiVA.org:mdh-21410DiVA, id: diva2:647602
Available from: 2013-09-11 Created: 2013-09-11 Last updated: 2017-12-06Bibliographically approved

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Funk, Peter

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