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Objective. BP neural network (BPNN) model and support vector machine (SVM) model were used to predict the total hospitalization expenses of patients with bronchopneumonia. Methods. A total of 355 patients with bronchopneumonia from January 2018 to December 2020 were collected and sorted out. The data set was randomly divided into a training set ( n = 249 ) and a test set ( n = 106 ) according to 7 : 3. The BPNN model and SVM model were constructed to analyze the predictors of total hospitalization expenses. The effectiveness was compared between these two prediction models. Results. The top three influencing factors and their importance for predicting total hospitalization cost by the BPNN model were hospitalization days (0.477), age (0.154), and discharge department (0.083). The top 3 factors predicted by the SVM model were hospitalization days (0.215), age (0.196), and marital status (0.172). The area under the curve of these two models is 0.838 (95% CI: 0.755~0.921) and 0.889 (95% CI: 0.819~0.959), respectively. Conclusion. Both the BPNN model and SVM model can predict the total hospitalization expenses of patients with bronchopneumonia, but the prediction effect of the SVM model is better than the BPNN model.

Objective: The self-care ability of puerpera is poor, and their health knowledge of maternal and infant and care skills is relatively poor. The aim of our study was to investigate the effect of health information integration based on network platform in the postpartum maternal and infant health care. Methods: A total of 80 maternal women admitted to our hospital from September 2018 to March 2019 were randomly divided into a control group and a study group, with 40 patients in each group. The puerpera in control group received regular telephone visits after discharge. The puerpera in study group received health information integration based on network platform. The uterus recovery of puerpera in two groups at 42 days postpartum, as well as the lochia, bloating, nipple splitting and breastfeeding behaviors were compared. The time of jaundice regression and umbilical cord detachment of neonates in t two groups, as well as the incidence of facial eczema and umbilical inflammation were compared. Results: The uterus recovery rate and exclusive breastfeeding rate of puerpera in study group were higher than those in the control group at 42 days postpartum, and the incidences of abnormal lochia, swollen breasts, and nipple splitting were lower than those in the control group. The difference between the two groups was statistically significant (P < 0.05). The neonates in study group were lower than the observation group in terms of the days of jaundice regression, facial eczema, and umbilical inflammation. The difference between the two groups was statistically significant (P < 0.05). However, there was no significant difference in the days of umbilical cord shedding (P > 0.05). Conclusions: The health information integration based on network platform in postpartum maternal and infant health care can effectively improve maternal breastfeeding compliance and reduce the adverse symptoms of maternal and neonatal discharge.