Retrieving stroke risk factors based on intellectual analysis of electronic health records
- 作者: Donitova V.V.1, Kireev D.A.1, Kobrinskii B.A.1, Smirnov I.V.1, Titova E.V.1
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隶属关系:
- Federal Research Center “Computer Science and Control” of Russian Academy of Sciences
- 期: 卷 73, 编号 2 (2023)
- 页面: 111-122
- 栏目: System analysis in medicine and biology
- URL: https://journal-vniispk.ru/2079-0279/article/view/287002
- DOI: https://doi.org/10.14357/20790279230211
- ID: 287002
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详细
Stroke is the world’s second leading cause of death and the third leading cause of disability and death combined. Risk factors for stroke are potentially manageable so prevention of this disease is possible. Identification of previously unknown modifiable risk factors for stroke or testing the significance of known factors is an urgent task that should be solved based on a retrospective analysis of the electronic health records of patients with this disease. The paper presents an approach to identifying risk factors for acute cerebrovascular accidents from texts of case histories using natural language processing and machine learning methods. The proposed approach made it possible to identify risk factors for stroke and transient ischemic attack in patients of one of the Moscow clinics. The identified factors are consistent with those found in other studies.
作者简介
V. Donitova
Federal Research Center “Computer Science and Control” of Russian Academy of Sciences
编辑信件的主要联系方式.
Email: vdonitova@gmail.com
Researcher
俄罗斯联邦, MoscowD. Kireev
Federal Research Center “Computer Science and Control” of Russian Academy of Sciences
Email: kireev@isa.ru
Programmer
俄罗斯联邦, MoscowB. Kobrinskii
Federal Research Center “Computer Science and Control” of Russian Academy of Sciences
Email: kba_05@mail.ru
PhD, Professor
俄罗斯联邦, MoscowI. Smirnov
Federal Research Center “Computer Science and Control” of Russian Academy of Sciences
Email: ivs@isa.ru
PhD, Assoc. Professor
俄罗斯联邦, MoscowE. Titova
Federal Research Center “Computer Science and Control” of Russian Academy of Sciences
Email: elz.titova@gmail.com
research engineer
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