Intelligent system for diabetes prediction in patients with chronic pancreatitis
- Authors: Shesternikova O.P.1, Agafonov M.A.2, Vinokurova L.V.2, Pankratova E.S.3, Finn V.K.3
-
Affiliations:
- OOO NVA-Tsentr
- Moscow Clinical Research Center
- All-Russian Institute of Scientific and Technical Information
- Issue: Vol 43, No 5-6 (2016)
- Pages: 315-345
- Section: Article
- URL: https://journals.rcsi.science/0147-6882/article/view/175152
- DOI: https://doi.org/10.3103/S0147688216050051
- ID: 175152
Cite item
Abstract
This paper presents the results of the JSM-method for automated support of scientific research (ASSR JSM-method) implemented in a computer intelligent system (IS-JSM), which predicts the development of diabetes in patients with chronic pancreatitis. For the first time the ASSR JSM-method is applied to a sequence of expanding databases of facts, which was used for the detection of empirical regularities (ERs), viz., preserved causes of the studied effect (development of diabetes in patients with chronic pancreatitis). To recognize ERs in the IS-JSM, we used an algebraic lattice of JSM-reasoning strategies (inductive inference rules). These results have an informative clinical interpretation and prove the usefulness of data mining using the IS-JSM, which can be used as a tool for evidence-based medicine.
About the authors
O. P. Shesternikova
OOO NVA-Tsentr
Author for correspondence.
Email: oshestemikova@gmail.com
Russian Federation, Moscow
M. A. Agafonov
Moscow Clinical Research Center
Email: oshestemikova@gmail.com
Russian Federation, Moscow
L. V. Vinokurova
Moscow Clinical Research Center
Email: oshestemikova@gmail.com
Russian Federation, Moscow
E. S. Pankratova
All-Russian Institute of Scientific and Technical Information
Email: oshestemikova@gmail.com
Russian Federation, Moscow
V. K. Finn
All-Russian Institute of Scientific and Technical Information
Email: oshestemikova@gmail.com
Russian Federation, Moscow
Supplementary files
