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Sub-health state is a state of health and low quality between disease and health. The theoretical basis of children's sub-health is to start from the whole. The common clinical sub-health conditions cannot be explained by modern detection methods, and it can be screened and analyzed with the help of big data in medical informatization. The combination of "Internet + " and the health care model is an innovation in the construction of medical informatization. It can provide many considerate services to the masses in time and alleviate the anxiety of illness. Therefore, it is very necessary to carry out the efficacy evaluation of children's sub-health from the perspective of medical information. Therefore, this paper completes the following work with the help of AI neural network: (1) This paper proposes an improved AlexNet network evaluation method based on attention mechanism. In this study, attention mechanism is added to the original AlexNet model to weight each channel of the feature layer. At the same time, we improve the large convolution kernel of the previous layers of the original AlexNet network and use batch normalization instead of the local response normalization (LRN) layer in the original model. (2) This paper proposes an evaluation method based on improved residual network, which improves the original residual block of the residual model and widens the residual block. The residual block can effectively reduce the amount of network parameters and improve the efficiency of network training. (3) This paper proposes an evaluation method of multi-scale feature fusion (MSFF). The features extracted from the improved AlexNet and residual network are fused and then evaluated. At this time, the training time is greatly shortened, and the accuracy is higher than that of single model. [ABSTRACT FROM AUTHOR]

A meta‐analysis investigation was executed to measure the outcome of sutured wounds (SWs) compared with tissue adhesive (TA) for paediatric wound closure (PWC). A comprehensive literature inspection till February 2023 was applied and 2018 interrelated investigations were reviewed. The 18 chosen investigations enclosed 1697 children with PWC in the chosen investigations' starting point, 977 of them were utilising SWs, and 906 were utilising TA. Odds ratio (OR) in addition to 95% confidence intervals (CIs) were used to compute the value of the effect of SWs compared with TA for PWC by the dichotomous approaches and a fixed or random model. SWs had significantly higher wound cosmetic (WC) scores (mean deviation [MD], 1.70; 95% CI, 0.57–2.84, P =.003), lower wound dehiscence (WD) (OR 0.60; 95% CI, 0.06–0.43, P <.001), and lower cost (MD, −10.22; 95% CI, −10.94 to −9.50, P <.001) compared with those with TA in PWC. No significant difference was found between children utilising SWs and TA in wound infection (WI) (OR, 0.45; 95% CI, 0.15–1.30, P =.14) with no heterogeneity (I2 = 0%) in PWC. SWs had significantly higher WC scores, lower WD, and lower cost, yet, no significant difference was found in WI compared with those with TA in PWC. However, care must be exercised when dealing with its values because of the low sample size of some of the nominated investigations and the low number of selected investigations for the meta‐analysis. [ABSTRACT FROM AUTHOR]