Weight Loss as Therapeutic Option to Restore Fertility in Obese Men: A Meta-Analytic Study by Daniele Santi, Carla Greco, Arcangelo Barbonetti, Manuela Simoni, Mario Maggi, Giovanni Corona

“…Weight loss resulted in a significant increase of sperm concentration (effect size 0.495, standard error 0.251 [0.003, 0.986], p=0.049) and progressive motility (effect size 0.567, standard error 0.372 [0.370, 0.764], p<0.001). …”

Automatic Recognition of Motor Skills in Triathlon: A Novel Tool for Measuring Movement Cadence and Cycling Tasks by Stuart M. Chesher, Carlo Martinotti, Dale W. Chapman, Simon M. Rosalie, Paula C. Charlton, Kevin J. Netto

“…<b>Results</b>: The peak-counting algorithm successfully detected 98.7% of swimming strokes, with a root mean square error of 2.7 swimming strokes. It detected 97.8% of cycling pedal strokes with a root mean square error of 9.1 pedal strokes, and 99.4% of running strides with a root mean square error of 1.2 running strides. …”
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Predictive modeling of air quality in the Tehran megacity via deep learning techniques by Abdullah Kaviani Rad, Mohammad Javad Nematollahi, Abbas Pak, Mohammadreza Mahmoudi

“…R-squared (R2), root-mean-square error (RMSE), mean absolute error (MAE), and mean-square error (MSE) were used to assess and compare the models. …”
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Development and validation of a novel AI-derived index for predicting COPD medical costs in clinical practice by Guan-Heng Liu, Chin-Ling Li, Chih-Yuan Yang, Shih-Feng Liu

“…Model performance was assessed with Mean Squared Error (MSE), Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), and R-squared (R²). …”
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Deep learning models for hepatitis E incidence prediction leveraging Baidu index by Yanhui Guo, Li Zhang, Shengnan Pang, Xiya Cui, Xuechen Zhao, Yi Feng

“…The performance of models are evaluated by three standard quality metrics, including root mean square error(RMSE), mean absolute percentage error(MAPE) and mean absolute error(MAE). …”
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Comparison of ARIMA model and XGBoost model for prediction of human brucellosis in mainland China: a time-series study by Wei Wu, Peng Guan, Mirxat Alim, Guo-Hua Ye, De-Sheng Huang, Bao-Sen Zhou

“…The training set was composed of the monthly incidence of human brucellosis in mainland China from January 2008 to June 2018, and the test set was composed of the monthly incidence from July 2018 to June 2019. The mean absolute error (MAE), root mean square error (RMSE) and mean absolute percentage error (MAPE) were used to evaluate the effects of model fitting and prediction.Results The number of human brucellosis patients in mainland China increased from 30 002 in 2008 to 40 328 in 2018. …”
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Cross-cultural adaptation, validity, and reliability of the Danish version of the neurophysiology of pain questionnaire by Nikolaj Agger, Thor Andre Brøndberg Stæhr, Michael Skovdal Rathleff, Lene Baad-Hansen, Shellie Boudreau, David Høyrup Christiansen

“…Internal consistency was evaluated using Cronbach’s alpha, while test-retest reliability was determined using the intraclass correlation coefficient (ICC). Measurement error was analyzed using the standard error of measurement (SEM) and minimal detectable change (MDC). …”
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Evaluation of the impact of COVID-19 on hepatitis B in Henan Province and its epidemic trend based on Bayesian structured time series model by Xinxiao Li, Yanyan Li, Shushuo Xu, Penghao Wang, Meng Hu, Haibin Li, Yongbin Wang

“…It was also found that the average absolute error, root mean square error, and root mean square percentage error generated by the BSTS model were smaller than ones generated by the ARIMA model. …”
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Tissue gene expression analysis approach in a context of high technical and biological heterogeneity by Evan Bagley, Souvik Seal, Lauren R. Fanning, Jean-Sebastien Anoma, Tami Crawford, Benjamin G. Vincent, Elizabeth L. Barry, Martha J. Shrubsole, Erin Kirk, John A. Baron, Dale C. Snover, David N. Lewin, Todd A. Mackenzie, Xiaohua Gao, Melissa A. Troester, Alexander V. Alekseyenko, Kristin Wallace

“…While NSDiff labeled twice as many significant genes as RUVg, suggesting greater sensitivity, it also exhibited higher Type I error rates and increased computational demand. Conclusions RUVg achieved a balance between computational efficiency and low Type I error, while NSDiff was more sensitive but computationally demanding and exhibited higher Type I error. …”
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Can the number of confirmed COVID-19 cases be predicted more accurately by including lifestyle data? An exploratory study for data-driven prediction of COVID-19 cases in metropolit... by Sungwook Jung

“…Conclusions Through this study, we were able to identify three notable results that could contribute to predicting the number of patients infected with epidemic in the future.…”
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Quality of Snow Cover Characteristics Derived from ERA 5-Land Reanalysis for the Territory of Perm Krai by A. D. Kryuchkov, N. A. Kalinin, I. A. Sidorov

“…For 30 years, the magnitude of the reanalysis error decreased as it was compared with 61% observation points. …”
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Quantitative assay for ciprofloxacin and enrofloxacin formulations by Saundria Moed, Mackenzie Hall, Norman Lee, Clarissa Prazeres da Costa, Ernst K Rødland, Atena I Shemirani, Katie Clifford, Darash Desai, Muhammad H Zaman

“…We extended this assay to assess the quality of enrofloxacin (enro), another fluoroquinolone primarily used in veterinary medicine, within 5% error of the package indication. # Conclusions These assays can be used to assess the quality of cipro and enro tablets in the field and identify substandard tablets, potentially helping to remove those tablets from circulation and decrease acceleration of AMR to cipro and enro. …”
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Comparison of broth microdilution, broth disk elution and automated system results in determining vancomycin susceptibilities of Staphylococcus aureus strains by Tuğba Ayvalık, Emel Sesli Çetin

“…The major and very major error rates of the automated system was found to be 5% and 0% respectively (Table 2). …”
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Analysis of corn price forecast in China based on Lasso-XGBoost-SHAP by Wenming Cheng, Fangyuan Li

“…The study’s methodological framework and core conclusions are in the below graphical abstract. Results demonstrate that the Lasso-XGBoost model outperforms traditional linear models (LM) and other algorithms, including SVM (Support Vector Machine) and MLP (Multilayer Perceptron), with root mean squared error (RMSE) of 0.094, coefficient of determination (R2) of 0.973, mean absolute error (MAE) of 0.072, representing a 7.84% reduction in RMSE compared to standalone XGBoost. …”
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Work-related exhaustion and telomere length: a population-based study. by Kirsi Ahola, Ilari Sirén, Mika Kivimäki, Samuli Ripatti, Arpo Aromaa, Jouko Lönnqvist, Iiris Hovatta

“…The association between exhaustion and relative telomere length remained significant after additional adjustment for marital and socioeconomic status, smoking, body mass index, and morbidities (adjusted difference 0.044 relative units, standard error of the mean 0.017, p = 0.008).<h4>Conclusions</h4>These data suggest that work-related exhaustion is related to the acceleration of the rate of biological aging. …”
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FINANCIAL AND ECONOMIC SAFETY OF ECONOMIC AGENTS by V. I. Avdiysky, V. M. Bezdenezhnyh, V. E. Liechtenstein, G. V. Ross, K. I. Solodovnikova

“…The article discusses the sources of error of the indicators and tests of the security of economic agents, the mechanisms, which make them inadequate are identifi ed. …”
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A machine learning method to monitor China's AIDS epidemics with data from Baidu trends. by Yongqing Nan, Yanyan Gao

“…Three criteria, the mean absolute percentage error, the root mean squared percentage error, and the index of agreement, are used to test the forecasting performance of the ANN method.…”
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Corrigendum: The new views on the state of the gut microbiota in obesity and diabetes mellitus type 2 (Diabetes mellitus. 2019;22(3). doi: 10.14341/DM10194) by Elena V. Pokrovskaya, Minara S. Shamkhalova, Marina V. Shestakova

“…Front Microbiol. 2017;8:563. doi: https://doi.org/10.3389/fmicb.2017.00563&raquo; is listed twice (№№ 7 and 13) in the list of references.The authors apologize for this error and state that this does not change the scientific conclusions of the article in any way.The original article has been updated.…”
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Comparisons of Visual and Surgical Outcomes after Reuse or Replacement of Dislocated in-the-Bag Intraocular Lens by Takayuki Baba, Tomohiro Nizawa, Toshiyuki Oshitari, Shuichi Yamamoto

“…The pre- and postoperative parameters analyzed included the visual acuity, refractive error, corneal endothelial cell density, and intraocular pressure (IOP). …”
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Accuracy Evaluation of a Stereolithographic Surgical Template for Dental Implant Insertion Using 3D Superimposition Protocol by Corina Marilena Cristache, Silviu Gurbanescu

“…Conclusions. The surgical template used has proved high accuracy for implant insertion. …”
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