Predicting Iran Cooperative Development Bank's Profit/Loss: Two-stage Collective Learning by Seyed Bagher Fattahi, Seyed Mozafar Mirbargkar, Ebrahim Chirani, Mohammadreza Vatanparast

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Enhancing urban air quality prediction using time-based-spatial forecasting framework by Shrikar Jayaraman, Nathezhtha T, Abirami S, Sakthivel G

“…The outcomes demonstrate the TBS model’s ability to accurately predict AQI values. The integration of CNNs and time series model allowed for an clearer and deeper understanding of geographical and pollutant concentration factors that contribute to air quality variations.…”
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Analysis of the predictive value of the prostate-specific antigen-to-neutrophil ratio for the diagnosis of prostate cancer by Yuxuan Chen, Haisheng Yan, Yaoqin Xu, Kexin Chen, Runqin Yang, Jiali Yang, Ruian Zhu, Rui Lin, Jiang Wang, Jie Liu, Pingsheng Gao, Lei Pang, Lexin Wang

“…Objective In this study, we explored the predictive value of prostate-specific antigen-to-neutrophil ratio (PNR) for the diagnosis of prostate cancer, with a view to further improving the diagnostic accuracy of prostate cancer. …”
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Interpretable Machine Learning Approaches for Forecasting and Predicting Air Pollution: A Systematic Review by Anass Houdou, Imad El Badisy, Kenza Khomsi, Sammila Andrade Abdala, Fayez Abdulla, Houda Najmi, Majdouline Obtel, Lahcen Belyamani, Azeddine Ibrahimi, Mohamed Khalis

Subjects: “…Air quality prediction…”
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Interval combined prediction of mine tunnel's air volume considering multiple influencing factors. by Zhen Wang, Erkan Topal, Liangshan Shao, Chen Yang

“…The tunnel air volume and influencing factors are then input into different neural networks for air volume prediction. To further improve prediction accuracy, the predicted values of wind volume intervals from the single prediction method are transformed into triangular fuzzy numbers, and the generalized induced ordered weighted average operator is introduced for the combination of prediction results. …”
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Drone Video Anomaly Detection by Future Segmentation Prediction and Spatio- Temporal Relational Modeling by Ahmed Fakhry, Janghoon Lee, Jong Taek Lee

Subjects: “…future segmentation prediction…”
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Machine learning-driven optimization for predicting compressive strength in fly ash geopolymer concrete by Maryam Bypour, Mohammad Yekrangnia, Mahdi Kioumarsi

“…This study employs machine learning (ML) techniques to predict the compressive strength (fc′) of fly ash-based geopolymer concrete, utilizing a comprehensive set of experimental data. …”
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Role of Computed Tomography in Predicting Programmed Death Ligand-1 Positivity in Gastric Adenocarcinoma by Yu ZH, Ma WQ, Ren JW, Zhang XT, Chu L

“…A nomogram was developed to assess the model’s predictive performance, which was evaluated using the receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA). …”
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Prediction models for cognitive impairment in middle-aged patients with cerebral small vessel disease by Wei Zheng, Xiaoyan Qin, Ronghua Mu, Peng Yang, Bingqin Huang, Bingqin Huang, Zhixuan Song, Xiqi Zhu, Xiqi Zhu

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Predicting Depression: a comparative study of machine learning approaches based on language usage. by Luciana Mariñelarena-Dondena, Edgardo Ferretti, Manolis Maragoudakis, Maximiliano Sapino, Marcelo Luis Errecalde

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Biliary Atresia Treatment: Can Shear Wave Elastography Predict Kasai Procedure Outcomes? by Sekarsari Damayanti, Gema Ramadhan Muhammad, Rinaldhy Kshetra, Prihartono Joedo

“…This underlines the significance of our study in investigating shear wave elastography as a predictive tool for the success of Kasai procedure in biliary atresia patients. …”
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XGBoost-enhanced ensemble model using discriminative hybrid features for the prediction of sumoylation sites by Salman Khan, Sumaiya Noor, Tahir Javed, Afshan Naseem, Fahad Aslam, Salman A. AlQahtani, Nijad Ahmad

“…This study introduces XGBoost-Sumo, a robust model to predict sumoylation sites by integrating protein structure and sequence data. …”
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Apriori algorithm based prediction of students’ mental health risks in the context of artificial intelligence by You Fu, Fang Ren, Jiantao Lin

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Predictive Model of Purpose of Life in Adolescents of Public Educational Institutions from Arequipa City by Julio Cesar Huamani Cahua, Walter L. Arias Gallegos, Ana Lucía Núñez Cohello

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A Study on the performance of Four Regression Models in Predicting Weather Temperature Based on Python by Li Taobei

“…Performance metrics were used to evaluate the models' predictive capacity. With the highest R2 value and the lowest error metrics, Random Forest Regression fared better than the other models, suggesting higher predictive accuracy, according to the data. …”
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Using resistor network models to predict the transport properties of solid-state battery composites by Lukas Ketter, Niklas Greb, Tim Bernges, Wolfgang G. Zeier

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Serum adropin levels as a potential biomarker for predicting diabetic kidney disease progression by I-Wen Chen, I-Wen Chen, Cheng-Wei Lin, Cheng-Wei Lin, Cheng-Wei Lin, Chia-Ni Lin, Chia-Ni Lin, Szu-Tah Chen, Szu-Tah Chen, Szu-Tah Chen

“…BackgroundTo investigate the value of serum adropin in predicting chronic kidney disease (CKD) progression in subjects with type 2 diabetes (T2D).Materials and methodsSerum adropin levels were measured in normal control and T2D patients with various stage of CKD. …”
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Learning-based pattern-data-driven forecast approach for predicting future well responses by Yeongju Kim, Baehyun Min, Alexander Sun, Bo Ren, Hoonyoung Jeong

“…ECS addresses the conditioning and prediction variance issues of LDFA and LPFA by combining predictions of multiple learning models and screening out predictions that do not sufficiently honor observed data. …”
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Correction: Empirical prediction intervals applied to short term mortality forecasts and excess deaths by Ricarda Duerst, Jonas Schöley

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Construction and validation of risk prediction models for renal replacement therapy in patients with acute pancreatitis by Fei Zuo, Lei Zhong, Jie Min, Jinyu Zhang, Longping Yao

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