Preparation and capacitor optimization of MnO2/AC using I-optimal coordinate exchange model by Tilahun Temesgen, Eneyew Tilahun Bekele, Bedasa Abdisa Gonfa, C.R. Ravikumar, Lemma Teshome Tufa, Syed Khasim, Dereje Tsegaye, H.C. Ananda Murthy, Yilkal Dessie

“…This indicates the strong correlation between the actual and predicted values, and the proposed model is statistically significant. …”
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Optimization of the Encapsulation of Lemuru Fish Protein Hydrolysate by Spray-Drying Using Response Surface Methodology by Ayu Hanifah, Wawan Kosasih, Diah Ratnaningrum, Dian Andriani, Herlian Eriska Putra, Yellianty Yelliantty, Sri Priatni

“…The actual results also fall well within the confidence interval of the predicted values, confirming the robustness of the model and the reliability of the predicted optimal encapsulation conditions. …”
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Comparative analysis of digital mammography and contrast-enhanced mammography in diagnosing suspicious breast calcifications: implications for surgical decision-making by Marwa Mohamed Taher Mohamed ElSayad, Maha Hussein Mohamed Helal, Omar Hussein Omar, Ahmed Gamal Eldeen Othman, Marwa Elsayed Abdelrahman Ibrahim

“…Calculated sensitivity, specificity, positive and negative predictive values and total accuracy of DM were 91.4%, 70.8%, 62.7%, 93.9%, and 78% respectively as compared to 85.7%, 90.7%, 83.3%, 92.2%, and 89% for CEM. …”
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Using statistical analysis to evaluate enterprise performance in the Python programming environment by O. G. Konyukova, F. F. Baratova

“…The presented calculations will not only allow timely and promptly react to changes in the external economic environment of activity, but also adjust costs to already predicted values, which, in turn, will help to increase the profitability of the enterprise, which is the main task of any owner.   …”
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Application of Machine Learning Models for the Early Detection of Metritis in Dairy Cows Based on Physiological, Behavioural and Milk Quality Indicators by Karina Džermeikaitė, Justina Krištolaitytė, Ramūnas Antanaitis

“…Models were evaluated based on accuracy, sensitivity, specificity, positive and negative predictive values (PPV, NPV), area under the receiver operating characteristic (ROC) area under the curve (AUC), and Matthews correlation coefficient (MCC). …”
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Establishment of a Generalizable Industrial Crop Model for Microwave Extraction of Unsaturated Fatty Acids by Junyi Chen, Didi Lu, Shiqiang Chen, Song Liu, Yaqiu Zhang, Conghong Zhan

“…The stability and accuracy of the model were verified by the orthogonal experiment of UFA extraction from rice, and the correlation coefficient between the predicted value and the actual value of the orthogonal experiment was 0.9998. …”
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Value of Contrast-Enhanced Ultrasound in Adjusting the Classification of Chinese-TIRADS 4 Nodules by Hong Cheng, Shuang-Shuang Zhuo, Xin Rong, Ting-Yue Qi, Hong-Guang Sun, Xiao Xiao, Wen Zhang, Hai-Yan Cao, Lin-Hai Zhu, Lei Wang

“…The sensitivity, specificity, accuracy, and positive and negative predictive values of the C-TIRADS classification for the diagnosis of thyroid nodule malignancy before the adjustment based on the CEUS results were 83.6%, 63.8%, 74.4%, 72.7%, and 77.1%, respectively, and these values were 91.0%, 82.8%, 87.2%, 85.9%, and 88.9%, respectively, after the adjustment. …”
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Performance measures of the medical priority dispatch system in an urban basic life support system by Vittorio Nicoletta, Maxime Robitaille-Fortin, Valérie Bélanger, Éric Mercier, Jessica Harrisson

“…We assessed system performance using sensitivity, specificity, overtriage, undertriage, predictive values, and accuracy. Statistical analyses included chi-square tests for priority consistency and pairwise t-tests for performance changes over time. …”
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Prospects of application of artificial neural networks for forecasting of cargo transportation volume in transport systems by D. T. Yakupov, O. N. Rozhko

“…The neural network model consists of a hidden layer of neurons with a sigmoidal activation function and an output neuron with a linear activation function, the input values of the dynamic time series, and the predicted value is removed from the output. For a more objective assessment of the prospects of the ANN application, the results of the forecast are presented in comparison with the results obtained in predicting the method of exponential smoothing.Results. …”
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Global, regional, and national burden of knee osteoarthritis: findings from the Global Burden of Disease study 2021 and projections to 2045 by Yi Ouyang, Miaomiao Dai

“…Notably, the case number of these metrics were predicted to keeping increasing, with predicted values of 658,088,384.48 (322,110,040.98–994,066,727.98), 47,256,502.97 (23,440,017.7–71,072,988.23) and 20,517,479.78 (10,056,930.68–30,978,028.88), respectively. …”
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Comparative Study on Total Organic Carbon Content Logging Prediction Method Based on Machine Learning by TANG Shengshou, YANG Bin, JIN Jiulong, LIU Hongrui, DAI Xingyu, PU Jincheng

“…The analysis of the practical application effect showed that the conventional Δlog R method had poor accuracy in calculating the total organic carbon content and could not achieve the expected effect. The predicted value of the XGBoost prediction model is in the best agreement with the measured value and has the highest reliability. …”
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Prospective validation of an artificial intelligence assessment in a cohort of applicants seeking financial compensation for asbestosis (PROSBEST) by Illaa Smesseim, Kevin B. W. Groot Lipman, Stefano Trebeschi, Martijn M. Stuiver, Renaud Tissier, Jacobus A. Burgers, Cornedine J. de Gooijer

“…Secondary objectives included evaluating specificity, accuracy, predictive values, area under the curve of the receiver operating characteristic (ROC-AUC), area under the precision-recall curve (PR-AUC), and interobserver variability. …”
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Construction and validation of a prognostic prediction model for osteosarcoma in children based on the SEER database by ZHANG Lei, LI Yuwan, WU Yindan, XU Zhi, SHAO Jinfu

“…The calibration curve showed that the predicted values were highly consistent with the observed values. …”
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External validation of precisebreast, a digital prognostic test for predicting breast cancer recurrence, in an early-stage cohort from the Netherlands by Pieter J. Westenend, Claudia Meurs, Gerardo Fernandez, Marcel Prastawa, Abishek Sainath Madduri, Aaron Feliz, Juan Carlos Mejias, Alexander Shtabsky, Xiaozhu Zhang, Brandon Veremis, Rebecca DeAngel, Michael J. Donovan

“…Model performance was assessed by AUC/C-index, hazard ratios, sensitivity, specificity, and negative and positive predictive values (NPV and PPV, respectively). Results PDxBR showed prognostic accuracy in this external cohort (AUC/C-index 0.71, 95% CI: 0.66–0.75). …”
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Clinical characteristics and prognosis of primary small cell carcinoma of the breast: a propensity score-matched, population-based study by Lei Yin, Ai-Hong Yin, Chen-Chen Pu

“…The calibration curve in the ROC analysis indicated that the predicted value was consistent with the actual observation value. …”
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Study of the diagnostic and prognostic value of parameters of cytokine profile, oxidative stress and cytogenetic abnormalities in patients with tick-borne infections by E. N. Ilyinskikh, O. V. Voronkova, K. V. Samoylov, A. V. Semenova, R. R. Hasanova, Yu. I. Bulankov, V. N. Nekrasov, E. I. Petrova, G. N. Kolganova

“…The parameters showed from average to excellent predictive ability as well as high positive and negative predictive values.Conclusion. In patients with tick-borne encephalitis, we detected correlations between the pyrexia levels and the biomarkers of inflammation, oxidative stress, and cytogenetic damage as well as it were found some differences in these parameters from the group of borreliosis patients, which probably had prognostic significance.…”
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Combination of PSA density and MLR improves the diagnostic accuracy of prostate cancer by Feng Guo, Aerken Maolake, Zecheng Ni, Xun Li, Bide Liu, Zetian Tang, Zhenfeng Shi, Jiuzhi Li

“…The area under the curve (AUC) increased when PSAD was combined with MLR in patients with PSA 4–10 ng/mL and patients with PSA 10–22 ng/mL, and the positive predictive values were 81.81% and 90.91%, respectively (P = 0.0008 and P = 0.0002). …”
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D-dimer serves as predictor of plastic bronchitis or necrotizing pneumonia in children with Mycoplasma pneumoniae pneumonia by Yanke Yue, Tiantian Lian, Lei Kang, Shuai Liu, Wenjin Geng, Meixian Xu

“…Receiver operating characteristic (ROC) analysis showed that the best cutoff point for D-dimer in predicting PB or NP is 2.44 (mg/L) (AUC = 0.85, 95% CI: 0.76–0.95, sensitivity: 92.31%, specificity: 75.53%, P < 0.001*).ConclusionsThis study found that the elevated DD level (≥2.44 mg/L) has a predicting value for the progression of children with MPP to the composite outcome of PB or NP. …”
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Novel integrative models to predict the severity of inflammation and fibrosis in patients with drug-induced liver injury by Yue Zhang, Chuan Lu, Jingying Xu, Qiqi Ma, Mei Han, Li Ying

“…This study aims to develop novel integrative models to identify DILI-associated liver inflammation and fibrosis, and compare the predictive values with previously developed indexes.MethodsA total of 72 DILI patients diagnosed as DILI through liver biopsy were enrolled in this study. …”
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THE CRITERIA FOR LYMPH NODE METASTATIC DISEASE IN UTERINE CERVIX CANCER PATIENTS BASED ON MRI FINDINGS by E. G. Zhuk, I. A. Kosenko

“…The sensitivity and specificity with a cutoff of ≥0.8cm were 68 % (CI 48.3‑82.9) and 80 % (CI 63.8‑90.3), respectively; the positive and negative predictive values were 71 % and 78 %, respectively; and the accuracy was 75 % (CI 62.7‑84.3). …”
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