Effect of AI deep learning techniques on possible complications and clinical nursing quality of patients with coronary heart disease

Abstract To analyze the effect of AI deep learning techniques on understanding possible complications and improving clinical nursing quality of patients with coronary heart disease. The clinical data of 182 patients with coronary heart disease who received treatment were collected, among which 80 patients received routine nursing management only during hospitalization, set as the control group; AI deep learning techniques were applied to the other 102 patients During treatment and nursing, the incidence of related complications in the control group was higher than that in the observation group, and the average hospitalization time of the patients was longer than that in the observation group. In the observation group, AI deep learning techniques were applied to predict the incidence of complications of coronary heart disease in 14 patients, with an accuracy rate of 87.50% (14/16) and an error rate of 12.50% (2/16). Both the clinical nursing quality and patients’ satisfaction score of the observation group were higher than those of the control group, and the overall nursing satisfaction rate of the patients was higher. Applied in prediction of possible complications of hospitalized patients with coronary heart disease, AI deep learning techniques were of high accuracy rate.