A Hybrid Case-Based System in Stress Diagnosis and Treatment
2012 (English)Manuscript (preprint) (Other academic)
Computer-aided decision support systems play anincreasingly important role in clinical diagnosis and treatment.However, they are difficult to build for domains where thedomain theory is weak and where different experts differ indiagnosis. Stress diagnosis and treatment is an example of such adomain. This paper explores several artificial intelligencemethods and techniques and in particular case-based reasoning,textual information retrieval, rule-based reasoning, and fuzzylogic to enable a more reliable diagnosis and treatment of stress.The proposed hybrid case-based approach has been validated byimplementing a prototype in close collaboration with leadingexperts in stress diagnosis. The obtained sensitivity, specificityand overall accuracy compared to an expert are 92%, 86% and88% respectively.
Place, publisher, year, edition, pages
Artificial intelligence, Biofeedback, Case based reasoning, Diagnosis, Information retrieval, Rule based reasoning, Stress measurement.
Computer and Information Science
Research subject Computer Science
IdentifiersURN: urn:nbn:se:mdh:diva-13161OAI: oai:DiVA.org:mdh-13161DiVA: diva2:450594
IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI2012)
Submitted to: IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI2012)2011-10-212011-10-212014-02-04Bibliographically approved