Computed Tomography and Statistical Health Informatics Analysis of Helicobacter pylori Infection in Gastrointestinal Patients
Objective: We statistically analyzed the status of Helicobacter pylori infection in patients with gastroenterology and its correlation with gastrointestinal diseases in order to control the infection rate and reduce gastrointestinal diseases using health informatics and
computer tomography (CT). Methods: CT images from March 2014 to April 2016 were selected to analyze the incidence of 184 patients in the hospital. Among them, 78 cases of H. pylori infection were compared. We concluded that we compared clinical data and distribution of H.
pylori age, disease type, smoking, drinking, and other gastrointestinal diseases. Results: The positive rate was 42.39%. Linear regression models showed that age, occupation, smoking, alcohol consumption, and gastrointestinal diseases were risk factors for Helicobacter pylori
infection in patients with gastrointestinal diseases (P < 0.05). Both duodenal and gastric ulcers were positive. Higher than the positive rate of other gastrointestinal diseases. The positive rate of Helicobacter pylori in gastric polyps is lower than other gastrointestinal
diseases. Results obtained by detailed analysis of difference statistics using CT imaging (P < 0.05). Conclusions: Strengthening the screening of Helicobacter pylori infection in patients with digestive medicine and analyzing its correlation with gastrointestinal diseases
is an effective way to prevent the occurrence of H. pylori. It is of great value to reduce the infection rate and prevent the occurrence of gastrointestinal diseases. We eventually confirmed this using CT image analysis.
Keywords: COMPUTER TOMOGRAPHY; GASTROINTESTINAL DISEASES; HELICOBACTER PYLORI; INFECTION; LINEAR REGRESSION
Document Type: Research Article
Publication date: 01 December 2020
- Journal of Medical Imaging and Health Informatics (JMIHI) is a medium to disseminate novel experimental and theoretical research results in the field of biomedicine, biology, clinical, rehabilitation engineering, medical image processing, bio-computing, D2H2, and other health related areas.
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