Intelligent system for diabetes prediction in patients with chronic pancreatitis
- 作者: Shesternikova O.P.1, Agafonov M.A.2, Vinokurova L.V.2, Pankratova E.S.3, Finn V.K.3
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隶属关系:
- OOO NVA-Tsentr
- Moscow Clinical Research Center
- All-Russian Institute of Scientific and Technical Information
- 期: 卷 43, 编号 5-6 (2016)
- 页面: 315-345
- 栏目: Article
- URL: https://journals.rcsi.science/0147-6882/article/view/175152
- DOI: https://doi.org/10.3103/S0147688216050051
- ID: 175152
如何引用文章
详细
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.
作者简介
O. Shesternikova
OOO NVA-Tsentr
编辑信件的主要联系方式.
Email: oshestemikova@gmail.com
俄罗斯联邦, Moscow
M. Agafonov
Moscow Clinical Research Center
Email: oshestemikova@gmail.com
俄罗斯联邦, Moscow
L. Vinokurova
Moscow Clinical Research Center
Email: oshestemikova@gmail.com
俄罗斯联邦, Moscow
E. Pankratova
All-Russian Institute of Scientific and Technical Information
Email: oshestemikova@gmail.com
俄罗斯联邦, Moscow
V. Finn
All-Russian Institute of Scientific and Technical Information
Email: oshestemikova@gmail.com
俄罗斯联邦, Moscow
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