A visual positioning method for tunnel boring machines in underground coal mines based on anchor net features by Xuhui ZHANG, Yunkai CHI, Yuyang DU, Junying JIANG, Wenjuan YANG, Youjun ZHAO, Jicheng WAN, Yanqun WANG, Chenhui TIAN

“…Additionally, the root mean square error (RMSE) decreased from 0.531 to 0.426, suggesting a reduction of 19.8%. …”
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Regional MRI Perfusion Measures Predict Motor/Executive Function in Patients with Clinically Isolated Syndrome by Efrosini Z. Papadaki, Panagiotis G. Simos, Vasileios C. Mastorodemos, Theodora Panou, Thomas G. Maris, Apostolos H. Karantanas, Andreas Plaitakis

“…On the set shifting condition of the respective task significant, positive associations were found between error rates and CBV values in the semioval center and periventricular NAWM bilaterally. …”
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Quantifying optimal inner limiting membrane peeling in macular hole surgery: a machine learning framework for predictive modeling and schematic visualization by Xiang Zhang, Hongjie Ma, Song Lin, Ledong Zhao, Lu Chen, Zetong Nie, Zhaoxiong Wang, Chang Liu, Xiaorong Li, Wenbo Li, Bojie Hu

“…Model performance was assessed using root mean squared error (RMSE), mean squared error (MSE), mean absolute error (MAE), and the coefficient of determination (R²). …”
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Feasibility Assessment of Using Smart Trackers in Telemedicine Systems to Remotely Monitor the Overall Health of Patients in Real-Time by I. V. Pospelova, I. V. Cherepanova, D. S. Bragin, V. N. Serebryakova

“…In order to avoid the high error in measuring systolic pressure, an algorithm for assessing the general health of patients was developed. …”
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Adaptation of Everyday Discrimination Scale (EDS) for Nurses: A Validity and Reliability Study in Turkish by Nazan Ulusoy, Hatice Ulusoy, Albert Nienhaus, Patrick Brzoska

“…It improved significantly after addition of two error covariances between items 1 and 2 and items 7 and 8 (RMSEA= 0.051; CFI= 0.982; TLI= 0.973; SRMR= 0.036). …”
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Improving TerraClimate hydroclimatic data accuracy with XGBoost for regions with sparse gauge networks: A case study of the Meknes plateau and the Middle Atlas Causse, Morocco by Hammoud Yassine, Allali Youssef, Saadane Abderrahim

“…Applying the XGBoost algorithm significantly improves the raw TerraClimate data, reducing the average Mean Absolute Error (MAE) across all parameters from 3.08 to 0.29, and the average Root Mean Square Error (RMSE) from 4.84 to 0.46, and increasing the average Nash-Sutcliffe Efficiency (NSE) from 0.82 to 0.99. …”
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How digital therapeutic alliances influence the perceived helpfulness of online mental health Q&A: An explainable machine learning approach by Yinghui Huang, Hui Liu, Maomao Chi, Sujie Meng, Weijun Wang

“…Results The machine learning-based model for predicting perceived helpfulness demonstrated strong performance, achieving an root mean square error of 0.8234 and a mean absolute percentage error of 22.7288%. …”
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Accuracy of intertrochanteric osteotomy for patients with slipped capital femoral epiphysis operated with 3D printed patient-specific guides by M. van den Boorn, J. G. G. Dobbe, V. Lagerburg, M. M. E. H. Witbreuk, G. J. Streekstra

“…Rotational malalignment improved from 29–63⁰ preoperatively to 15–31⁰ postoperatively. Residual error was mostly attributed to plate malposition, with residual translation in the range of 3–13 mm and rotation of 8–28⁰. …”
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Ship motion identification model based on enhanced Bi-LSTM by Haozhe ZHANG, Zhibo YANG, Xuguo JIAO, Chengxing LÜ, Peng LEI

“…Finally, using the navigation data of KLVCC2 ships, the prediction effects of the enhanced Bi-LSTM model are compared with those of the Support Vector Machine (SVM), Gate Recurrent Unit (GRU), and long short-term memory (LSTM) models.ResultsThe Root Mean Square Error (RMSE) and Mean Absolute Error (MAE) performance indicators of the enhanced Bi-LSTM model in the test set are lower than 0.015 and 0.011 respectively, and the coefficient of determination（R2）is higher than 0.99913, demonstrating prediction accuracy significantly higher than that of the SVM, GRU, and LSTM models.ConclusionThe proposed enhanced Bi-model has excellent generalization performance and excellent prediction stability and precision, and effectively realizes ship motion identification.…”
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A Method for Predicting the Main Indicators of Cardiopulmonary Stress Testing for Patients with Chronic Heart Failure by A. S. Krasichkov, E. Mbazumutima, F. Shikama, E. M. Nifontov

“…Based on the analysis of the data obtained, a method for assessing the peak values of HR and of PC of the patients with chronic heart failure was developed.Conclusion. The relative error of the proposed estimate of the HR peak in most cases was no more than 10 %, which allows it to be used for practical purposes. …”
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Published population pharmacokinetic models of mycophenolate sodium: a systematic review and external evaluation in a Chinese sample of renal transplant recipients by Tong Gao, Wen Xu, Xiao Li, Qie Guo, Donghua Liu, Xiaolei Zhang, Ping Leng, Jialin Sun

“…In the goodness-of-fit diagnosis and prediction error test based on model prediction, the population prediction data of all models were not good, while the individual prediction data showed that the fitting result of Model 1 was relatively better. …”
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Effect of Capsular Tension Ring on Refractive and Morphological Outcomes in Pseudoexfoliative Eyes by Cunha B, Gil P, Rodrigues Alves N, Hipólito-Fernandes D, Maduro V, Feijão J, Alves N

“…In Group 2, a significant hyperopic shift (p=0.035) and 12% of eyes with a prediction error above 1D was observed, which were not seen in Groups 1 or 3. …”
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Comparison of the Effectiveness of Gamification, Tracking Patterns, and Visual Gauges in Improving Hand Motor Performance Through Biofeedback by Ayda Ebrahimi, Amir Salar Jafarpishe, Mohsen Vahedi, Marzieh Izadi Laybidi, Somayeh Mohammadi

“…Statistical analysis was conducted using the paired t-test to compare the root mean square error between groups. Results: The pattern-tracking group demonstrated significant motor performance improvement, with a statistically significant difference in root mean square error (P<0.001). …”
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Comparison of Predictability in Vault Using NK Formula and KS Formula for the Implantable Collamer Lens Surgery by Xin Zhong, Yan Li, Yuancun Li, Geng Wang, Yali Du, Mingzhi Zhang

“…The two formulas showed no statistically significant difference in absolute prediction error (APE). Conclusion. The NK formula exhibited superior consistency and low predictive error compared to the KS formula in the 12.6 mm ICL group. …”
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Multiple category-lot quality assurance sampling: a new classification system with application to schistosomiasis control. by Casey Olives, Joseph J Valadez, Simon J Brooker, Marcello Pagano

“…In the fourth study, where these designs performed poorly (kappa-statistic less than 0.50), the majority of observations fell in regions where potential error is known to be high. Employment of semi-curtailed and curtailed sampling further reduced the sample size by as many as 0.5 and 3.5 observations per school, respectively, without increasing classification error.…”
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Research on RF Intensity Temperature Sensing based on 1D-CNN by DING Meiqi, GUI Lin, WANG Ziyi, SHANG Disen, QIAN Min, LI Qiankun

“…Compared with the traditional Gaussian fitting algorithm, the demodulation speed of the 1D-CNN-based algorithm is improved by 2.72 times. 1D-CNN shows high stability and low error under different temperature conditions.【Conclusion】1D-CNN has significant advantages in dealing with complex nonlinear relationships and feature extraction, not only superior in computational efficiency and robustness, but also effective in dealing with noise and environmental interference. …”
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Assessment of executive functions of poisoning following suicide by Nastaran Eizadi-Mood

“…Continuous performance tests (CPTs) including commission error components, omission response, correct response, and response time were used to evaluate EFs. …”
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Impact of agricultural industry transformation based on deep learning model evaluation and metaheuristic algorithms under dual carbon strategy by Xuan Zhao, Weiyun Tang, Qiuyan Liu, Hongtao Cao, Fei Chen

“…Across various climatic conditions, the average prediction error remains below 2.5%, indicating strong adaptability and stability. …”
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Spatial Interpolation Methods of Temperature Data Based on Geographic Information System—Taking Jiangxi Province as an Example by Zihao Feng, Runjie Wang, Xianglei Liu, Ming Huang, Liang Huo

“…At the same time, the method of cross-validation was adopted, and the average error and the root-mean-square error were quoted as the evaluation indexes for accuracy assessment. …”
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Methods for assessing integral parameters of arterial stiffness: comparative analysis and new potential by Yu. E. Teregulov, E. A. Atsel, M. S. Maksimova, N. V. Maksumova, S. N. Prokopyeva, F. R. Chuvashaeva

“…This made it possible to calculate the dependence of Ev on SAC and E∑ using regression analysis.Conclusion. Using linear regression, the formula for calculating the Ev using SAC was obtained, which has a high accuracy at a heart rate of 60 to 90 bpm (error, no more than ±5%). …”
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