A machine learning–based risk prediction model for atrial fibrillation in critically ill patients by Laith Alomari, MD, Yaman Jarrar, MD, Zaid Al-Fakhouri, MD, Emmanuel Otabor, MBBS, Justin Lam, MD, Jana Alomari

“…Model performance was evaluated using accuracy, area under the receiver-operating characteristic curve (AUROC), and predictive values. SHAP (Shapley Additive exPlanations) analysis interpreted individual feature contributions to the model's predictions. …”
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Aggregation-Based Ensemble Classifier Versus Neural Networks Models for Recognizing Phishing Attacks by Wojciech Galka, Jan G. Bazan, Urszula Bentkowska, Kamil Szwed, Marcin Mrukowicz, Pawel Drygas, Lech Zareba, Marcin Szpyrka, Piotr Suszalski, Sebastian Obara

“…Aggregation functions are employed to integrate the prediction values of classification models applied in the email phishing problem. …”
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Pattern of Pulmonary Dysfunctions in Craniovertebral Junction Anomaly and Its Persistence after Rigid Occipitocervical Fixation by Shaam Bodeliwala, Vikas Nagar, Hukum Singh, Daljit Singh, Anita Jagetia, Sharad Pandey, Rajesh Ruttala, Pankaj Kumar

“…The mean values of FVC, FEV1, FEF25–75% were 72, 68, and 71% of their mean predicted values, with FEV1% in the range of 70 to 95% with a mean of 81.4%. …”
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Improving intraoperative diagnosis of spread through air spaces: A cryo-embedding-medium inflation method for frozen section analysisCentral MessagePerspective by Takashi Eguchi, MD, Shunichiro Matsuoka, MD, Mai Iwaya, MD, PhD, Shota Kobayashi, MD, Maho Seshimoto, MD, Shuji Mishima, MD, Daisuke Hara, MD, Hirotaka Kumeda, MD, Kentaro Miura, MD, PhD, Kazutoshi Hamanaka, MD, Takeshi Uehara, MD, PhD, Kimihiro Shimizu, MD, PhD

“…The sensitivity, specificity, positive and negative predictive values, and accuracy of FS slides for STAS detection were 81%, 89%, 81%, 89%, and 86%, respectively. …”
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Data-driven soil salinization mapping: risk prediction and uncertainty quantification based on Bayesian inference by Yujian Yang, Ying Zhao, Rongjiang Yao, Xueqin Tong

“…KDE of 100 groups of predicted values showed a good fit based on data-driven soil EC, higher levels of uncertainty associated with soil EC correspond to areas where the gaussian distributions overlap using Theano, as PyMC3 core component based on deep learning principles.…”
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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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Efficacy and Safety of Anti-Interleukin-5 Therapy in Patients with Asthma: A Systematic Review and Meta-Analysis. by Fa-Ping Wang, Ting Liu, Zhu Lan, Su-Yun Li, Hui Mao

“…<h4>Conclusions</h4>Anti-interleukin 5 monoclonal therapies for asthma could be safe for slightly improving FEV1 (or FEV1% of predicted value), quality of life, and reducing exacerbations risk and blood and sputum eosinophils, but have no significant effect on PEF, histamine PC20, and SABA rescue use. …”
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COMPREHENSIVE ASSESSMENT OF THE MORTALITY OF THE POPULATION OF THE RUSSIAN FEDERATION AND KUZBASS FROM MYOCARDIAL INFARCTION FOR THE PERIOD 2012-2020 by Андрей Георгиевич Петров, Сергей Анатольевич Макаров, Николай Владимирович Абрамов, Сергей Николаевич Филимонов, Василий Васильевич Кашталап, Виктор Андреевич Семенихин

“…Logarithmic curves are selected for specific time series, which would most accurately reflect the features of the actual dynamics. The predicted values of mortality from myocardial infarction in Kuzbass and the Russian Federation were calculated. …”
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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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Flow cytometry for screening and prioritisation of urine samples: a retrospective comparison with culture by Vicky Sender, John Kerr White, Ludvig Bolinder, Karin Amilon, Mirja Hägg, Karin Haij Bhattarai, Niklas K. Björkström, Baharak Saeedi

“…Receiver operating characteristic (ROC) curve analyses assessed method agreement across different patient subpopulations. Predictive values were calculated for the total population and the ten different subpopulations at different cut-offs. …”
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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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Auditory evoked potential wave VI as an objective indicator of sedation depth in neonates undergoing chloral hydrate sedation: a double-blind randomized controlled study by Zong Zheng, Shanpu Yang, Hongyan Liu, Zhimin Sheng

“…The receiver operating characteristic (ROC) curve was used to evaluate the predictive ability of wave VI latency in deep sedation, analyzing its sensitivity, specificity, and predictive values.ResultsIn the treatment group, wave VI disappearance rates increased in a sedation-dependent manner across the Ramsay Sedation Scale: 0% at level 4, 26% at level 5, and 68.6% at level 6 (p &lt; 0.05). …”
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Clinical value of calibrated abdominal compression plus transthoracic echocardiography to predict fluid responsiveness in critically ill infants: a diagnostic accuracy study by Julien Gotchac, Anouk Navion, Yaniss Belaroussi, Roman Klifa, Pascal Amedro, Julie Guichoux, Olivier Brissaud

“…At this threshold value, sensitivity was 92% (95%CI 62–100), specificity was 87% (95%CI 60–98), positive and negative predictive values were 85% (95%CI 60–95) and 93% (95%CI 66–99) respectively. …”
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A systematic review and meta-analysis of the diagnostic accuracy after preimplantation genetic testing for aneuploidy. by Vanessa Bacal, Angela Li, Heather Shapiro, Urvi Rana, Rhonda Zwingerman, Lisa Avery, Alina Palermo, Eleni Philipoppolous, Crystal Chan

“…For preclinical studies, the main outcome was the positive and negative predictive values. Misdiagnosis rate was the outcome for pregnancy outcome studies. …”
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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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