Development of Predictive Nomograms for Clinical Use to Quantify the Risk of Amputation in Patients with Diabetic Foot Ulcer by Bocheng Peng, Rui Min, Yiqin Liao, Aixi Yu

“…Finally, the performance of the prediction model was evaluated and verified by receiver working characteristic (ROC) curve, corrected calibration curve, and clinical decision curve. …”
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Investigating Tree Family Machine Learning Techniques for a Predictive System to Unveil Software Defects by Rashid Naseem, Bilal Khan, Arshad Ahmad, Ahmad Almogren, Saima Jabeen, Bashir Hayat, Muhammad Arif Shah

“…Tree family machine learning techniques are well-thought-out to be one of the finest and ordinarily used supervised learning methods. In this study, different tree family machine learning techniques are employed for software defect prediction using ten benchmark datasets. …”
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Effects of oral maintenance chemotherapy and predictive value of circulating EBV DNA in metastatic nasopharyngeal carcinoma by Han Zhou, Tianzhu Lu, Qiaojuan Guo, Yan Chen, Mengwei Chen, Yansong Chen, Yingying Lin, Chuanben Chen, Liqin Ma, Yun Xu, Shaojun Lin, Jianji Pan

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Geophysical Log Responses and Predictive Modeling of Coal Quality in the Shanxi Formation, Northern Jiangsu, China by Xuejuan Song, Meng Wu, Nong Zhang, Yong Qin, Yang Yu, Yaqun Ren, Hao Ma

“…Traditional coal quality assessment methods rely exclusively on the laboratory testing of physical samples, which impedes detailed stratigraphic evaluation and limits the integration of intelligent precision mining technologies. …”
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Predictive Factors and Nomogram for 30-Day Mortality in Heatstroke Patients: A Retrospective Cohort Study by Anxin Li, Yuchen Zhang, Xiaoshi Zhang, Zixiao Duan, Yan Chen, Xiaoyan Jiang, Wuquan Deng

“…Methods: We conducted a retrospective cohort study, analyzing the clinical data of 203 HS patients between May 2016–September 2024. …”
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A predictive model for body water and fluid balance using 3D smartphone anthropometry by Austin J. Graybeal, Abby T. Compton, Sydney H. Swafford, Caleb F. Brandner, Molly F. Johnson, Maria G. Kaylor, Hunter Haynes, Jon Stavres

“…Smartphone-derived ICF was calculated as the difference between smartphone-predicted TBW and ECF. Fluid overload and imbalance were determined using ECF/TBW and ECF/ICF, respectively, and subsequently predicted from the retained variables using receiver operating characteristic curve analyses and logistic regression.ResultsEstimates from each of the newly-developed prediction models were not significantly different from the estimates produced using BIS (all p ≥ 0.70) and revealed acceptable agreement (TBW: R2 = 0.91, RMSE = 3.24 L; ECF: R2 = 0.94, RMSE = 1.10 L; ICF: R2 = 0.87, RMSE = 2.29 L) when evaluated in the testing sample (n = 66), although proportional bias was observed (p < 0.001). …”
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Development of a predictive risk model for all-cause mortality in patients with diabetes in Hong Kong by William Ka Kei Wu, Tong Liu, Ian Chi Kei Wong, Qingpeng Zhang, Jiandong Zhou, Sharen Lee, Keith Sai Kit Leung, Kamalan Jeevaratnam, Wing Tak Wong

“…Machine and deep learning approaches were used to improve overall survival prediction and were evaluated with fivefold cross validation method.Results A total of 273 678 patients (mean age: 65.4±12.7 years, male: 48.2%, median follow-up: 142 (IQR=106–142) months) were included, with 91 155 deaths occurring on follow-up (33.3%; annualized mortality rate: 3.4%/year; 2.7 million patient-years). …”
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The Predictive Value of Soluble Fms-Like Tyrosine Kinase-1 for Prognosis in COVID-19 Patients by Lai C, Wang Y, Shi F, Geng N, Liu Z, Pan W, Shi H, Ma Y, Liu B

“…Despite the availability of vaccines and treatments, effective biomarkers for predicting disease progression remain limited. This study aimed to investigate the prognostic value of soluble fms-like tyrosine kinase-1 (sFlt-1) in COVID-19 patients.Methods: A prospective cohort study was conducted involving 154 COVID-19 patients, with comprehensive clinical data and laboratory parameters analyzed to evaluate the effectiveness of sFlt-1 in determining disease severity and prognosis.Results: The results revealed that sFlt-1 levels correlated significantly with disease severity, showing higher levels in severe/critical cases compared to mild cases (P< 0.05). …”
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Nontraumatic headaches in the emergency department: identifying clinical associations and predictive warning signs of intracranial pathologies by Abdulaziz M. Alghamdi, Abdulkarim M. Alghamdi, Yousof Fahad Allarakia, Arwa S. Alghamdi, Abdulaziz S. Alrashid, Abdulwhab M. Alotaibi, Reem Addas, Ahmed I. Lary

“…BACKGROUND: Although headaches are common, only 3–21% are estimated to be secondary, with their causes ranging from non-alarming to life-threatening conditions. OBJECTIVES: Evaluate the associated factors and predictive warning signs of intracranial pathologies in patients presenting with nontraumatic headaches to the emergency document (ED). …”
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Metyrapone single administration, as a possible predictive tool of its dosage and timing in Cushing’s syndrome by Yasutaka Tsujimoto, Naoki Yamamoto, Hironori Bando, Masaaki Yamamoto, Yuka Ohmachi, Yuma Motomura, Yuka Oi-Yo, Yuriko Sasaki, Masaki Suzuki, Shin Urai, Michiko Takahashi, Genzo Iguchi, Wataru Ogawa, Hidenori Fukuoka

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Use of Saliva Analytes as a Predictive Model to Detect Diseases in the Pig: A Pilot Study by Eva Llamas-Amor, Alba Ortín-Bustillo, María José López-Martínez, Alberto Muñoz-Prieto, Edgar García Manzanilla, Julián Arense, Aida Miralles-Chorro, Pablo Fuentes, Silvia Martínez-Subiela, Antonio González-Bulnes, Elena Goyena, Andrea Martínez-Martínez, José Joaquín Cerón, Fernando Tecles

“…The aim of this research was to evaluate a panel of salivary analytes in three porcine diseases and establish predictive models to detect them. …”
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From helicobacter pylori to glucose metabolism: can DOB values serve as a predictive marker? by Yu Zhou, Jie Xu, Zhigang Huang, Daoxing He, Hui Duan, Yating Shi, Zhenjie Wang, Zhaoyi Chen

“…We investigated whether DOB could predict abnormal FBG in adults receiving routine health examinations.ObjectivesTo assess the association between H. pylori infection and metabolic abnormalities, and to evaluate the predictive utility of the DOB value for glycemic abnormalities.MethodsIn this retrospective study, 594 patients underwent both the 13C-UBT and metabolic parameter assessments. …”
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Predictive Value of IDEAL-IQ and DWI Imaging Biomarkers for P53 Mutations in Hepatocellular Carcinoma by Wang D, Yin H, Li X, Zhou S, Wang YC

“…Additionally, high-grade HCC showed significantly lower ADC values compared to lower-grade tumors (P &lt; 0.001).Conclusion: R2&amp;ast; and ADC exhibited significant features in P53-mutated HCC, suggesting their potential as non-invasive biomarkers for predicting P53 mutation status and guiding clinical management. …”
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Predictive value of peripheral blood piR-hsa-2700592 for prognosis of atrial fibrillation patients by YANG Lei, YANG Lei, WU Na, YANG Lanqing

“…Receiver operating characteristic (ROC) curve analysis (area under the curve, AUC), net reclassification index (NRI), and comprehensive discriminant improvement index (IDI) were used to evaluate the predictive performance, and decision curve analysis (DCA) was employed to assess the clinical benefit. …”
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Calculation Method of Axial Compressive Capacity of 7075-T6 Aluminum Alloy Rectangular Tubes Based on Continuous Strength Method by Zhiguan Huang, Hailin Li, Cheng Zhang, Junli Liu

“…The approach combining this modified curve with Chinese codes is termed the Modified Chinese Code Method. The axial capacities calculated by the CSM-based method, Modified Chinese Code Method, EN 1999-1-1, and AASTM were compared for accuracy evaluation. …”
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Predictive factors for outcome in HER2-low breast cancer patients after neoadjuvant chemotherapy by Yingbo Shao, Yingbo Shao, Huijuan Guan, Huijuan Guan, Zhifen Luo, Zhifen Luo, Yang Yu, Yang Yu, Yaning He, Yaning He, Qi Chen, Qi Chen, Chaojun Liu, Chaojun Liu, Fangyuan Zhu, Fangyuan Zhu, Hui Liu, Hui Liu

“…ObjectiveThe present study aimed to evaluate the predictive factors that predict outcomes of HER2-low breast cancer patients who did not achieve pathological complete response(pCR) after neoadjuvant chemotherapy (NAC).MethodsThis study included patients with HER2-low breast cancer who received NAC from January 2017 to December 2020. …”
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Comparison of the predictive capacity of the Alvarado and AIR scores in the diagnosis of acute appendicitis: A prospective study by L.M. Sanabria-Arévalo, L.C. Domínguez-Torres, J. Kock, J.D. Lotero, J.C. Gómez-Cáceres, E. Tuta-Quintero

“…The predictive capacity of the Alvarado and Air scores was evaluated through an ROC curve analysis, determining the area under the ROC curve. …”
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Predicting Financial Market Volatility with Modern Model and Traditional Model by R. G. Aldeki

“…Additionally, the effectiveness of the machine learning techniques’ selection and utilization of information in stock data is evaluated. Methods the semiparametric estimating technique known as support vector regression (SVR) has been widely used for the prediction of volatility in financial time series. …”
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Hyperparameter optimization of machine learning models for predicting actual evapotranspiration by Chalachew Muluken Liyew, Elvira Di Nardo, Stefano Ferraris, Rosa Meo

“…Consequently, AET data is limited, prompting the use of meteorological and soil features for prediction. This study develops and evaluates machine learning models for AET prediction based on two input combinations. …”
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A comparative study and simple baseline for travel time prediction by Chuang-Chieh Lin, Ming-Chu Ho, Chih-Chieh Hung, Hui-Huang Hsu

“…A multitude of studies have proposed methods to address this issue, yet these approaches often involve multiple stages and steps, including data preprocessing, feature selection, data imputation, prediction model. …”
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