Internal body temperature is the gold standard for the fever of pigs, however non-contact infrared imaging technology (IRT) can only measure the skin temperature of regions of interest (ROI). Therefore, using IRT to detect the internal body temperature should be based on a correlation model between the ROI temperature and the internal temperature. When heat exchange between the ROI and the surroundings makes the ROI temperature more correlated with the environment, merely depending on the ROI to predict the internal temperature is unreliable. To ensure a high prediction accuracy, this paper investigated the influence of air temperature and humidity on ROI temperature, then built a prediction model incorporating them. The animal test includes 18 swine. IRT was employed to collect the temperatures of the backside, eye, vulva, and ear root ROIs; meanwhile, the air temperature and humidity were recorded. Body temperature prediction models incorporating environmental factors and the ROI temperature were constructed based on Back Propagate Neural Net (BPNN), Random Forest (RF), and Support Vector Regression (SVR). All three models yielded better results regarding the maximum error, minimum error, and mean square error (MSE) when the environmental factors were considered. When environmental factors were incorporated, SVR produced the best outcome, with the maximum error at 0.478 °C, the minimum error at 0.124 °C, and the MSE at 0.159 °C. The result demonstrated the accuracy and applicability of SVR as a prediction model of pigs′ internal body temperature.

https://www.mdpi.com/1424-8220/20/15/4282/pdf

Non-Contact Evaluation of Pigs' Body Temperature Incorporating Environmental Factors.

To systematically evaluate the clinical effects of platelet-rich plasma in the treatment of lower limb venous ulcers by applying a meta-analysis method. The Pubmed, Cochrance Library, Embase, and OVID EBM Reviews databases were searched for the search terms'platelet-rich plasma" or "Plasma, Platelet-Rich" or "Platelet Rich Plasma" and "lower extremity venous ulcers' or "Leg Ulcers' or "Ulcer, Leg", and a meta-analysis was performed on the published research literature on platelet-rich plasma for lower extremity venous ulcers from January 1900 to April 2021. The outcome indicators were: post-treatment trauma area and healing rate. Revman 5.3 statistical software was applied for meta-analysis. A total of 294 patients with lower extremity venous ulcers were included in six publications, including 148 patients in the experimental group treated with PRP versus 146 patients in the control group treated with conventional therapy. There was a statistically significant difference in the Formula of an ellipse at the end of treatment (CM²) between the experimental group and the control group, with a mean difference of -1.19 (95% CI -1.80 to -0.58, P = .0001; 6 studies, 294 participants moderate quality of evidence). The difference between the healing rate of the experimental group and the control group was statistically significant, with a risk ratio (RR) of 5.73 (95% CI 3.29 - 9.99, P < .00001; 5 studies, 248 participants moderate quality of evidence).There may be publication bias for both Formula of an ellipse at the end of treatment and healing rate. This comprehensive meta-analysis of available evidence suggests that the application of PRP for lower extremity venous ulcers accelerates the wound healing process and improves wound healing rates.

Clinical Study of Platelet-Rich Plasma (PRP) for Lower Extremity Venous Ulcers: A Meta-Analysis and Systematic Review.

Clinical and radiologic outcomes after arthroscopic rotator cuff repair : Single-row versus speed-bridge technique

To systematically review of randomized controlled trials (RCTs) to compared the effects of leukocyte-rich and leukocyte-poor platelet-rich plasma in arthroscopic rotator cuff repair. Two independent reviewers comprehensively searched PubMed, Embase, and Cochrane library databases according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Comparison of leukocyte-rich platelet-rich plasma or leukocyte-poor platelet-rich plasma in rotator cuff repair in a level I RCTs. Methodological quality assessment was carried out using Cochrane Review Manager 5.3 software. P<0.05 was considered statistically significant. Nine RCTs with 540 patients were included in this review. Meta-analysis showed that leukocyte-poor platelet-rich plasma in significantly reduced retear rate in rotator cuff repair [RR=0.56 95% CI (0.42, 0.75); P<0.05), and in clinical results, the constant score [MD=3.67, 95% CI (1.62, 5.73); P=0.0005], UCLA score [MD=1.60, 95% CI (0.79, 2.42); P=0.0001], ASES score [MD=2.16, 95% CI (0.12, 4.20); P=0.04] were significantly improved. There was a significant result in favor of PRP for the Constant score [MD=-1.24, 95% CI (-1.50, -0.99); P<0.00001], while SST scores were not significantly different among all groups [MD=0.21, 95% CI (-0.21, 0.64); P=0.32]. In conclusion, leukocyte-poor platelet-rich plasma can improved the clinical function and reduced retear rate in arthroscopic rotator cuff repair. In contrast, the efficacy of leukocyte-rich platelet-rich plasma was not significantly improved with the exception of VAS score. 

Leukocyte-rich and Leukocyte-poor Platelet-rich Plasma in Rotator Cuff Repair: A Meta-analysis

The efficacy of platelet-rich plasma in arthroscopic rotator cuff repair: A protocol of randomized controlled trial.

The classification model of osteoporosis was established, the diagnostic index system of osteoporosis was analyzed, and the BP neural network system was designed. The data of 1261 people from 402 nuclear families were collected, including age, gender and medical history. The actual\n data were sampled and tested by using the computational function of ANN, so that the model error could be controlled within a set range. The results of neural network analysis suggested that among the 12 factors influencing bone mineral density, gender had the most obvious effect, followed\n by height, weight and age. The polymorphism of estrogen receptor PvuII had the greatest impact on bone mineral density (ER PvuII) of all candidate genes, and the factor that had the most serious effect was BGP gene. A large number of BP network training test results were within the expected\n error range, and the same conclusion was drawn using the same sample and traditional statistical methods.Therisk factors application has certain feasibility and accuracy.

Application of Back Propagation Neural Network Model in Prediction and Diagnosis of Osteoporosis

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The efficacy of platelet-rich plasma in arthroscopic rotator cuff repair: A protocol of randomized controlled trial.

Application of Back Propagation Neural Network Model in Prediction and Diagnosis of Osteoporosis