The aim was to analyze the infection, influencing factors, and clinical manifestations of Helicobacter pylori infection, coronary heart disease, and cytotoxin-associated protein A infection, so as to provide reference for the improvement of clinical diagnosis and treatment level of in-depth treatment. This paper presents a clinical observation method based on Helicobacter pylori infection, risk factors, and cytotoxin-associated protein A in patients with coronary heart disease. Methods. 237 patients with CHD diagnosed and tested by 14C breath test were selected from inpatients of cardiovascular diseases in a hospital for retrospective analysis. The clinical data, serum deepening indicators, Hcy, and other factors were analyzed through general condition investigation, previous history investigation, and physical examination. The patients were observed by the SPSS22.0 statistical data processing method. The results showed that among the respondents, 175 cases were HP-positive, the infection rate was 73.8%, 77 patients with stable angina pectoris were 64.9%, and 160 patients with acute coronary heart disease were 78.1%. The difference between the groups was statistically significant P < 0.05 . Conclusion. Helicobacter pylori cytotoxic-associated protein A can increase the risk of gastric cancer, and Helicobacter pylori eradication treatment is more conducive to reduce the incidence of gastric cancer and ensure the safety of patients.

This study was aimed to explore the value of the twin neural network model in the classification and recognition of cardiac ultrasound images of patients with atrial fibrillation. 80 patients with cardiac atrial fibrillation were selected and randomly divided into experimental group (40 cases) and control group (40 cases). The twin neural network (TNN) model was combined with traditional ultrasound, Doppler spectrum, tissue velocity, and strain imaging technology to obtain the patient’s cardiac structure parameters and analyze and compare related indicators. The results showed that the total atrial emptying fraction (TA-EF value) of the experimental group was 53.08%, which was significantly lower than that of the control group ( P < 0.05 ). There were no significant differences in left atrial diameter (LAD), left ventricular end-diastolic diameter (LVEDD), left atrial maximum volume (LAVmax), and left ventricular ejection fraction (LVEF) between the two groups. In the experimental group, the average peak velocity of mitral valve annulus (Em) was 8.49 cm/s, the peak velocity of lateral wall systole (Vs) was 6.82 cm/s, and the propagation velocity of left ventricular blood flow (Vp) was 51.2 cm/s, which were significantly reduced ( P < 0.05 ). The average values of peak strains in the middle and upper left atrium of the experimental group were significantly lower than those of the control group ( P < 0.05 ). It can be concluded that the combined use of the TNN model can more accurately and quickly classify and recognize ultrasound images.