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[Untitled]
- Source :
- Journal of Medical Systems. 25:119-131
- Publication Year :
- 2001
- Publisher :
- Springer Science and Business Media LLC, 2001.
-
Abstract
- Diabetes management by insulin administration is based on medical experts' experience, intuition, and expertise. As there is very little information in medical literature concerning practical aspects of this issue, medical experts adopt their own rules for insulin regimen specification and dose adjustment. This paper investigates the application of a neural network approach for the development of a prototype system for knowledge classification in this domain. The system will further facilitate decision making for diabetic patient management by insulin administration. In particular, a generating algorithm for learning arbitrary classification is employed. The factors participating in the decision making were among others diabetes type, patient age, current treatment, glucose profile, physical activity, food intake, and desirable blood glucose control. The resulting system was trained with 100 cases and tested on 100 patient cases. The system proved to be applicable to this particular problem, classifing correctly 92% of the testing cases.
- Subjects :
- Decision support system
Artificial neural network
business.industry
Insulin
medicine.medical_treatment
Medicine (miscellaneous)
Health Informatics
medicine.disease
Health informatics
Health Information Management
Diabetes management
Patient age
Diabetes mellitus
medicine
Operations management
Artificial intelligence
business
Information Systems
Medical literature
Subjects
Details
- ISSN :
- 01485598
- Volume :
- 25
- Database :
- OpenAIRE
- Journal :
- Journal of Medical Systems
- Accession number :
- edsair.doi...........1873d3180fc2f5ead3db846412db9c5b