Postoperative self-care ability of continuous nursing based on artificial intelligence for stroke patients with neurological injury

According to the statistics of relevant data, stroke is a relatively common cerebrovascular disease, and its incidence rate is as high as 185/100,000 to 219/100,000. Continuous care can improve the quality of life of stroke patients and reduce the rate of hospital visits and hospitalizations. In this study, patients in a local hospital of third-grade class-A hospital were used as cases. Artificial intelligence was used to conduct continuous nursing intervention for the patients who were discharged from the stroke by using the WeChat platform, regular follow-up and home care. Afterwards, the collected data were given a post-processing, independent-samples t-test for two groups. After 3 months of extended care, the BI (Barthel Index) score of the intervention group has increased by 23.87 points, and the depression self-rating scale score has decreased by 9.12 points. Compared with the control group, the patients' self-care ability, depression state, compliance with health guidance and laboratory indicators were also better than those in the control group, and the differences were statistically significant (P < 0.05). Compared with the control group, the trend of increasing the scores of each index was more significant in the intervention group.