The application of cluster nursing to prevent bacterial pneumonia in stroke patients in neurology department.

The research aims to explore the intervention effect of cluster nursing methods on bacterial pneumonia in stroke patients in neurology. A retrospective analysis is conducted on 120 patients diagnosed with stroke in the hospital from 2020 to 2022, who are diagnosed as stroke patients in the neurology department by doctors. 120 patients are randomly separated into a control group (CG) and a research group (RG) for the experiment, with 60 people in each group. The CG receive normal nursing; The RG adopt cluster nursing methods. Comparison have done in the general information, nursing satisfaction, physical improvement after intervention, and oral hygiene indicators of the 2 groups of patients, and the intervention effect of the 2 nursing methods on patients suffering from bacterial pneumonia is evaluated. When the time reached the 7th day, the nutritional risk screening scores of both groups were (9.53 ± 2.29) and (8.10 ± 2.12), respectively. The serum albumin levels were (36.46 ± 4.80) g/L and (34.16 ± 3.69) g/L, respectively. After simultaneous nursing intervention, there were P < .005 in respiratory rates in the 2nd and 4th months of intervention, as well as after the completion of nursing intervention. The respiratory rates of the RG patients improved toward a larger range of normal respiratory rates, with significant statistical significance (P < .005). As time passed, the number of people with shortness of breath in the CG increased sharply to 46, while those in the RG was only 27, indicating P < .05 between the 2 groups. At the beginning of the 3rd month, the satisfaction rates of the RG and the CG were (92.33 ± 1.17)% and (78.18 ± 1.07)%, respectively, and there was P < .0.05 between the 2 groups of data. The cluster nursing strategy has a significant relieving effect on bacterial pneumonia in stroke patients in the neurology department, which can effectively reduce the probability of pneumonia, improve their physical condition, and enhance their quality of life. It has certain clinical application value.

Application Analysis Based on Big Data Technology in Stroke Rehabilitation Nursing.

According to the statistical analysis, the incidence of stroke disease has gradually increased, particularly in recent years, which poses a huge threat to the safety of human life. Due to the advancement in science and technology specifically big data and sensors, a new research dome known as data mining technology has been introduced, which has the potential value from the perspective of large amount of data analysis. Information has become a new trend of science and technology, and data mining has been used in various application areas to analyze and predict strokes at home and abroad. In this study, big data technology is utilized to collect potential information and explores clinical pathways of level-3 rehabilitation in certain regions of China. Moreover, application effects of data mining in the rehabilitation of patients with the first ischemic stroke have been evaluated and reported. For this purpose, fifty (50) first-time ischemic stroke patients have been screened through big data and were nonartificially assigned to level-3 clinical pathway and conventional rehabilitation groups, respectively, specifically through software. The first group of patients enters the clinical path of the corresponding level according to the way of three-level referral. These patients were analyzed based on the collected results of completing the unified rehabilitation treatment plan of the three-level rehabilitation medical institution in the patient record form. The second group was selected according to the routine rehabilitation model and method of the medical institution where the patients visited were divided into four stages: before treatment, three weeks after treatment, nine weeks after treatment, and seventeen weeks after treatment. For this purpose, a simplified Fugl-Meyer analysis (FMA), recording of various functions of limb movement, and modified Barthel index (MBI) scale were used to analyze and evaluate the ability of daily activities and compare their effects. The final results showed that FMA and MBI scores of the two groups were improved in the three stages after treatment. The FMA and MBI scores of the clinical pathway group on 3rd and 9th weekends were significantly different from those of the conventional rehabilitation group (which is p < 0.05). Moreover, difference in FMA and MBI scores between the two at the 17th weekend was not significant. The total cost of the clinical pathway group, particularly at the ninth weekend, was higher than that of the conventional rehabilitation group, but the cost-benefit ratio was better and the incidence of complications was lower than that of the other group.

Application of Multi-Modal Imaging Mediated by Iron Carbon Nanoparticles Based on Reinforcement Learning in the Diagnosis of Breast Nodules.

Breast cancer has become the first malignant tumor in women. Early detection and early treatment are the key to improve the prognosis of breast cancer patients. The key to the screening and diagnosis of breast cancer lies in the qualitative differential diagnosis of breast nodules. With the rapid development of MRI technology, especially the application of high field strength and ultra-high field strength, the role of breast MRI is increasingly prominent. MRI has the advantages of safety, no ionizing radiation, high resolution of soft tissue, high sensitivity and specificity for the diagnosis of early breast cancer. Multimodal imaging based on reinforcement learning and iron carbon nanoparticles plays an important role in the diagnosis of breast nodules. This paper first discusses the application of iron carbon nanoparticles and breast MRI multimodal imaging technology in tumor treatment, and then studies the application of iron carbon nanoparticles mediated multimodal imaging in the diagnosis of breast nodules through experimental methods. The experimental results show that multimodal imaging has a good effect in the diagnosis of breast nodules, which is helpful for the prevention and treatment of breast nodules.