Effects of Out-of-Hospital Continuous Nursing on Postoperative Breast Cancer Patients by Medical Big Data

Abstract

This study aimed to explore the application value of the intelligent medical communication system based on the Apriori algorithm and cloud follow-up platform in out-of-hospital continuous nursing of breast cancer patients. In this study, the Apriori algorithm is optimized by Amazon Web Services (AWS) and graphics processing unit (GPU) to improve its data mining speed. At the same time, a cloud follow-up platform-based intelligent mobile medical communication system is established, which includes the log-in, my workstation, patient records, follow-up center, satisfaction management, propaganda and education center, SMS platform, and appointment management module. The subjects are divided into the control group (routine telephone follow-up, 163) and the intervention group (continuous nursing intervention, 216) according to different nursing methods. The cloud follow-up platform-based intelligent medical communication system is used to analyze patients’ compliance, quality of life before and after nursing, function limitation of affected limb, and nursing satisfaction under different nursing methods. The running time of Apriori algorithm is proportional to the data amount and inversely proportional to the number of nodes in the cluster. Compared with the control group, there are statistical differences in the proportion of complete compliance data, the proportion of poor compliance data, and the proportion of total compliance in the intervention group ( P < 0.05 ). After the intervention, the scores of the quality of life in the two groups are statistically different from those before treatment ( P < 0.05 ), and the scores of the quality of life in the intervention group were higher than those in the control group ( P < 0.05 ). The proportion of patients with limited and severely limited functional activity of the affected limb in the intervention group is significantly lower than that in the control group ( P < 0.05 ). The satisfaction rate of postoperative nursing in the intervention group is significantly higher than that in the control group ( P < 0.001 ), and the proportion of basically satisfied and dissatisfied patients in the control group was higher than that in the intervention group ( P < 0.05 ).

A Study on the Application of Extended Care Based on the Biopsychosocial Medicine Model in People with Abnormal Tumor Markers on Physical Examination

“…ose with abnormal tumor markers in physical examination do not understand the meaning of test results due to their lack of understanding of disease-related knowledge, or excessively interpret test results, resulting in significant changes in their psychological status, easy self-abandonment, and development of bad living habits and dietary habits, and some physical examinees may also experience insomnia due to negative emotional distress [15,16]. Continuing nursing based on the biopsychosocial medical model ensures that the physical examinees fully understand and master disease-related knowledge by establishing a nursing group, strengthening the communication between the group members and the physical examinees, and conducting health education oneon-one to the physical examinees, so that they can better cooperate to adjust bad living habits and go to the hospital for return visits in a timely manner [17].…”

“…The results showed that the compliance rate of disease-related knowledge score, regular return visit, reasonable diet, appropriate exercise, and regular routines of physical examination patients in the intervention group was higher than that in the control group ( P < 0.05), indicating that continuous nursing based on biopsychosocial medical model could improve disease-related knowledge and compliance behavior of patients with abnormal tumor markers in physical examination, promote their return visit on time, and maintain healthy living habits. Those with abnormal tumor markers in physical examination do not understand the meaning of test results due to their lack of understanding of disease-related knowledge, or excessively interpret test results, resulting in significant changes in their psychological status, easy self-abandonment, and development of bad living habits and dietary habits, and some physical examinees may also experience insomnia due to negative emotional distress [ 15 , 16 ]. Continuing nursing based on the biopsychosocial medical model ensures that the physical examinees fully understand and master disease-related knowledge by establishing a nursing group, strengthening the communication between the group members and the physical examinees, and conducting health education one-on-one to the physical examinees, so that they can better cooperate to adjust bad living habits and go to the hospital for return visits in a timely manner [ 17 ].…”

Health prognostics for lithium-ion batteries: mechanisms, methods, and prospects

“…Note that the sequence-to-sequence prediction framework can also adopt the iterative method when the predicted length is less than the remaining cycles. Since capacity is hard to measure in actual applications, capacity estimation is usually added before the sequence prediction, which can be realized by the SoH estimated methods summarized in the former section 213 .…”

“…Since capacity is hard to measure in actual applications, capacity estimation is usually added before sequence prediction, which can be realized by the SoH estimated methods summarized in the former section. 213 Due to the high sequential relationship of the capacity variation and the ease of implementation, sequence prediction for battery trajectory prediction has been developed rapidly in recent years. The iterative method for sequence-to-point prediction was combined with the Gray model to predict the future capacity, and PF was added for the uncertainty expression of the predicted lifetime by Chen et al 169,214 A similar idea was also shown in ref.…”

Construction and evaluation of a cloud follow-up platform for gynecological chemotherapy patients

“…Traditional follow-up methods, such as telephone, email, outpatient follow-up, family visit, and community follow-up, require a lot of human resources and time. Cloud follow-up can make up for these de ciencies and can realize patient information digital management, data processing, and sharing through information technology to save medical resources and improve the work e ciency of medical staff [12]. Follow-up is an essential part of gynecological chemotherapy patients' routine.…”