Relationship between helicobacter pylori infection and type 2 diabetes using machine learning BPNN mathematical model under community information management
| Autor: | Yuqiang Gao, Huan Ma, Eman Ghonaem, Shuhui Zhan, Juan Xiao, Zhaoxu Chen, Dong Tang, Mohammed Yousuf Abo Keir |
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| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Helicobacter pylori infection
medicine.medical_specialty Artificial intelligence QC1-999 General Physics and Astronomy Community information management health information platform 02 engineering and technology Urine Type 2 diabetes 01 natural sciences Excretion Mathematical model Internal medicine Diabetes mellitus 0103 physical sciences medicine 010302 applied physics Breath test medicine.diagnostic_test biology Helicobacter pylori business.industry Physics BPNN 021001 nanoscience & nanotechnology medicine.disease biology.organism_classification Clinical research 0210 nano-technology business |
| Zdroj: | Results in Physics, Vol 26, Iss, Pp 104363-(2021) |
| ISSN: | 2211-3797 |
| Popis: | Objective: This exploration aims to explore the effect of Helicobacter pylori infection on blood glucose mechanism and gastric function in patients with type 2 diabetes under the background of electronic medicine, and the effect of community information management platform on health management efficiency of patients with Helicobacter pylori, so as to lay the foundation for clinical research on Helicobacter pylori participation in the mechanism of type 2 diabetes. Methods: In this paper, 300 patients who were treated in our hospital from June 2016 to June 2019 were selected as the research object. Among them, 228 patients with type 2 diabetes were recorded as the experimental group, and 72 patients with non-type 2 diabetes were recorded as the control group. 13C breath test and serum IgG antibody test were performed on each research object. Patients infected with Helicobacter pylori in the experimental group were divided into groups according to the degree of urine albumin excretion. Urinary albumin excretion rate was |
| Databáze: | OpenAIRE |
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