To Evaluate the Effect of Structured Training Program about Premenstrual Syndrome on the Knowledge and Perception of Nursing Students at a Government Nursing Teaching Institute in... by Latika, Namita Batra, Pushpa Dahiya

“…Results: The pretest group exhibited a lower mean knowledge score (M = 25.0000, standard deviation (SD) =8.26225, standard error (SE) =0.55704) than the posttest group (M = 29.4773, SD = 9.64315, SE = 0.65014). …”
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Prevalence and Related Factors for Myopia in School-Aged Children in Qingdao by Jin Tao Sun, Meng An, Xiao Bo Yan, Guo Hua Li, Da Bo Wang

“…A total of 4890 (aged 10 to 15 years) students were initially enrolled in this study. 3753 (76.75%) students with completed refractive error and questionnaire data were analyzed. The children underwent a comprehensive eye examination. …”
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Validation of Amoxicillin iodometric procedure in quantitative analysis of pure substance and medical preparation by Yu. Yu. Serdiukova, O. V. Kolisnyk, Т. О. Tomarovska, S. M. Poluian, Z. V. Shovkova, O. H. Pohosian

“…The precision calculated as the relative standard deviation (RSD) was less than 0.8 % and accuracy (δ, relative error) was better than 0.4 %. The proposed method was validated statistically and through recovery studies. …”
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Impact of Digital Panoramic Radiograph Magnification on Vertical Measurement Accuracy by Marc El Hage, Jean-Pierre Bernard, Christophe Combescure, Lydia Vazquez

“…They also measured the implant lengths in two Digital Imaging Communications in Medicine viewers set at low (1.9 : 1), medium (3.4 : 1), and high (10 : 1) image magnifications. Results. The error between the measured length and the real implant length was close to zero for all three viewers and image magnifications. …”
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Procedural performance is linked to motor skills and language ability: Findings from a knot-tying task in children with and without developmental coordination disorder by Yu-Ting Tseng, Hsinjen Julie Hsu

“…These studies have largely relied on the serial reaction time paradigm, and results have not always been conclusive. This study examined procedural learning and its association with motor coordination and language ability in children with DCD and typically developing (TD) children, using an ecologically valid knot-tying task. …”
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Evaluation of Parametric and Non-Parametric Models in Estimating Canopy Cover Density of Zagros Forests Using Remote Sensing and Machine Learning by Sajad Alimahmoodi Sarab, MohamadHadi Moayery, MOhammad Mirzavand, Shaban Shataee Jouibary, Alireza Rashki

“…To compare the performance of these two models, the metrics RMSE, RMSE%, and R² were utilized.Results: The results indicated that the MLR model achieved an R² value of 0.54 and an RMSE% of 10.4 at a 0.05 confidence level, while the MLP model yielded an R² of 0.82 and an RMSE% of 4.5.Conclusions: The comparative analysis demonstrated that the artificial neural network (MLP) provided more accurate estimates with lower error rates than the multiple linear regression (MLR) method in predicting vegetation density.…”
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On the Evaluation of the Hyperthermic Efficiency of Magnetic Scaffolds by Matteo B. Lodi, Antonios Makridis, Konstantina Kazeli, Theodoros Samaras, Makis Angelakeris, Giuseppe Mazzarella, Alessandro Fanti

“…<italic>Results:</italic> From the simulations, we found that large overestimation in the SAR values can be found, due to the axial misplacement in the radiofrequency coil, while the radial misplacement has a lower impact on the estimated SAR value. <italic>Conclusions:</italic> The averaging of multiple temperature records is needed to reliably and effectively estimate the SAR of MagS for DST HT.…”
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Improved Sliding Mode Active Disturbance Rejection Control for Single-inductance Dual-output Buck Converter by HUANG Jinfeng, ZHOU Jie

“…Additionally, the steady-state error bounds of CRESO and the convergence time of the enhanced TSMC are derived.Results and DiscussionsA simulation and experimental platform for the SIDO Buck converter is established. …”
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Retrospective Clinical Trial to Evaluate the Effectiveness of a New Tanner–Whitehouse-Based Bone Age Assessment Algorithm Trained with a Deep Neural Network System by Meesun Lee, Young-Hun Choi, Seul-Bi Lee, Jae-Won Choi, Seunghyun Lee, Jae-Yeon Hwang, Jung-Eun Cheon, SungHyuk Hong, Jeonghoon Kim, Yeon-Jin Cho

“…Linear regression analysis was performed and the coefficient of determination (r²), mean absolute error (MAE), and root mean square error (RMSE) were measured. …”
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Batch gradient based smoothing L 2/3 regularization for training pi-sigma higher-order networks by Khidir Shaib Mohamed, Raed Muhammad Albadrani, Ekram Adam, Yan Xiong

“…We present the simulation results, which demonstrate that the smoothing L 2/3 regularization performs significantly better than the original L 2/3 regularization, thereby supporting the theoretical conclusions are offered as well.…”
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Development and validation of machine learning models for predicting post-cesarean pain and individualized pain management strategies: a multicenter study by Shenjuan Lv, Ning Sun, Chunhui Hao, Junqing Li, Yun Li

“…Performance metrics such as Root Mean Squared Error (RMSE) and Coefficient of Determination (R²) were evaluated through internal and external validations. …”
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Data Mining of 24-Hour Cumulative Precipitation Data in Iran Using Machine Learning: Multilayer Perceptron Neural Network and Decision Tree by mozaffar faraji, Majid Rezaii Banafsheh Daragh, Behroz sarisarraf, Ali Mohammad Khorshid Dust

“…The models’ performance was evaluated and compared with accuracy, precision, and error criteria. Results: The MLP model demonstrated efficiency in estimating monthly precipitation by minimizing MSE to 0.04. …”
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Assessing and Forecasting Natural Regeneration in Mediterranean Landscapes After Wildfires by Paraskevi Oikonomou, Vassilia Karathanassi, Vassilis Andronis, Ioannis Papoutsis

“…This combined analysis forms a methodology that allows drawing conclusions about the vegetation type that prevails after the fire. …”
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Individual psychological characteristics and features of coping with the disease in patients with the first psychotic episode and post-psychotic depression as targets for psychosoc... by E. Yu. Antokhin, A. V. Vasilyeva, T. A. Boldyreva, R. I. Antokhina

“…From the numerical characteristics of the samples, the arithmetic mean was determined with the calculation of the standard error of the mean, standard deviation. Statistically significant results were accepted at the p&lt;0.05 significance level.Conclusions: the study found a significant effect on the clinical manifestations of postpsychotic depression in patients who underwent PES of schizophrenia, all studied individual psychological characteristics with the highest coping activity, which indicates the undoubted involvement of reactive mechanisms in the development of this type of pathology. …”
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Independence on the lead of the identification of the ventricular depolarization in the electrocardiogram in wearable devices by Noemi Giordano, Silvia Cannone, Gabriella Balestra, Marco Knaflitz

“…Results: Compared against the Pan-Tompkins algorithm, our method reduced the absolute error between each lead and the first standard lead by 26 % to 64 % for the peak, and by 70 % to 82 % for the onset detection. …”
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Machine learning algorithms for predictive modeling of dyslipidemia-associated cardiovascular disease risk in pregnancy: a comparison of boosting, random forest, and decision tree... by Idris Zubairu Sadiq, Fatima Sadiq Abubakar, Muhammad Auwal Saliu, Babangida Sanusi katsayal, Aliyu Salihu, Aliyu Muhammad

“…Results The results showed that random forest regression outperformed both boosting and decision tree regression, recording the lowest error criteria (MSE = 0.071 and RMSE = 0.266) for evaluating the model. …”
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Influence of low-voltage electrical switching and protecting devices and parameters of electrical equipment on electricity losses in workshop power supply networks by E. Yu. Abdullazyanov, E. I. Gracheva, A. N. Gorlov, Z. M. Shakurova, A. G. Logacheva

“…The value of the relative error in determining the equivalent resistance of the busbar depending on the number of connected electric receivers and taking into account the studied parameters is calculated. …”
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Deep learning-based automated classification of choroidal layers in en face swept-source optical coherence tomography images by Je Moon Yoon, Ji Young Lim, Hoon Noh, Seung Wan Nam, Jee-Hyong Lee, Don-Il Ham

“…The developed algorithm successfully classified choroidal layers with a balanced accuracy of 84.30% and 92.61% within error ranges of 0 μm and 5.2 μm, respectively. Conclusions Automated stratification of choroidal layers from en face SS-OCT images can be achieved accurately through deep learning.…”
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Automatic Aortic Valve Extraction Using Deep Learning with Contrast-Enhanced Cardiac CT Images by Soichiro Inomata, Takaaki Yoshimura, Minghui Tang, Shota Ichikawa, Hiroyuki Sugimori

“…The aortic valve annulus area estimation had a mean error of 2.55 mm. Conclusions: Object detection showed superior performance in identifying the aortic valve annulus region, suggesting its potential for clinical application in cardiac imaging. …”
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Evaluation of Tru-Cut biopsy in differential diagnosis and challenges in breast adenoid cystic carcinoma on a case basis by İlyas Sayar, Ufuk Memiş, Sami Bilici, Nurten Arslan Isik

“…A diagnosis of AdCC was made with these findings. Conclusions. It is important to search for different patterns in addition to double cell population and pay attention to the material in the lumens in breast Tru-Cut biopsies that contain AdCC patterns that may cause the diagnosis of IBC and DCIS in error. …”
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