Comparative Evaluation of Presented Strength Criteria of Anisotropic Rocks Based on Triaxial Experiments by Yongfeng Liu, Zhengxing Yu, Yongming Yin, Jinglin Wen

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Microstructural diffusion MRI for differentiation of breast tumors and prediction of prognostic factors in breast cancer by Xiaoyan Wang, Yan Zhang, Jingliang Cheng, Liangjie Lin, Ying Hu, Anfei Wang, Yong Zhang, Ruhua Wang, Ying Li, Kun Zhang, Wenhua Zhang

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Advancing Geotechnical Evaluation of Wellbores: A Robust and Precise Model for Predicting Uniaxial Compressive Strength (UCS) of Rocks in Oil and Gas Wells by Mohammadali Ahmadi

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Evaluation of the potential of diffusion tensor imaging biomarkers in prediction of white matter changes after brain radiation therapy: A systematic review by Baranoosh Rahmani, Abdurrahim Rahimian, Mahsa Mansourian, Iraj Abedi

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Integrating proximal geophysical sensing and machine learning for digital soil mapping: Spatial prediction and model evaluation using a small dataset by Danilo César de Mello, Gustavo Vieira Veloso, Murilo Ferre de Mello, Marcos Guedes de Lana, Isabelle de Angeli Oliveira, Fellipe Alcantara de Oliveira Mello, Rafael Gomes Siqueira, Lucas Carvalho Gomes, Elpídio Inácio Fernandes-Filho, Carlos Ernesto Gonçalves Reynaud Schaefer, Márcio Rocha Francelino, Emilson Pereira Leite, Tiago Osório Ferreira, José Alexandre Melo Demattê

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ARTIFICIAL INTELLIGENCE IN UNIVERSITY MARKETING: SOME REALITIES AND POSSIBLE APPLICATIONS by Eudochia JOMIR, Grigore BELOSTECINIC

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Structural Response Evaluation of Krylov Subspace-Based Reduced-Order Model for Real-Time Structural Health Monitoring and Prediction of Container Ships by Kichan Sim, Byoung Wan Kim, Jeong Sam Han, Kangsu Lee

“…To address irregular wave loading challenges, we applied a snapshot-based Krylov subspace method. Unlike conventional methods that use unit force vectors in axial directions, this approach considers time-varying pressure distributions from irregular waves. …”
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Comparative evaluation of several toric intraocular lens calculators for predicting postoperative refractive astigmatism in cataract surgery: a real-world study by Haocheng Xian, Bingzhen Li, Ziyao Xia, Chun Zhang, Xuemin Li

“…Six toric IOL calculators were evaluated: Barrett toric calculator (with predicted PCA, measured PCA, and TK), Kane formula (predicted PCA), and EVO 2.0 formula (predicted and measured PCA). …”
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Evaluation of Prediction Models for the Capping and Breaking Force of Tablets Using Machine Learning Tools in Wet Granulation Commercial-Scale Pharmaceutical Manufacturing by Sun Ho Kim, Su Hyeon Han, Dong-Wan Seo, Myung Joo Kang

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Construction and evaluation of a nomogram prediction model for the risk of epistaxis following nasotracheal intubation: a single-center retrospective cohort study by Jie Chen, Hao Fan, Yuxing Wang, Yuhang Zhu, Ren Zhou, Hua Kang, Hong Jiang

“…Clinical data and imaging findings were collected, and the least absolute shrinkage and selection operator (LASSO) regression, followed by multivariate logistic regression analysis, were used to identify predictors of epistaxis. A nomogram prediction model was constructed, and its performance was evaluated using receiver operating characteristic (ROC) curves, the Hosmer–Lemeshow test, and decision curve analysis. …”
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Machine Learning-Driven Identification of Exosome-Related Genes in Head and Neck Squamous Cell Carcinoma for Prognostic Evaluation and Drug Response Prediction by Hua Cai, Liuqing Zhou, Yao Hu, Tao Zhou

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Prospective evaluation of mpMRI-derived nomograms for detecting prostate cancer in PI-RADS v2.1 upgraded and non-upgraded lesions by Ying Yi, Hang Wang, Dongliang Cheng, Zhifeng Xu, Xianhai Zhang, Chun Luo, Hai Zhao

“…BackgroundLimited data exist on the performance of Prostate Imaging Reporting and Data System (PI-RADS) v2.1 upgraded and non-upgraded lesions, both alone and in combined with multiparametric MRI (mpMRI) features, for prostate cancer detection.ObjectiveTo evaluate the rates of prostate cancer (PCa) and clinically significant prostate cancer(csPCa) rates in PI-RADS v2.1 upgraded and non-upgraded lesions, and to identify mpMRI features that improve detection accuracy.MethodsThis study included men who underwent mpMRI and ultrasound-guided (US-guided) biopsy from March 2023 to April 2024. …”
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Development and evaluation of a nomogram prediction model for invasion and metastasis in primary liver cancer based on serum CD147 and IL-6 by Wei Zhang, Di Wu, Xinping Wang, Hua Zhang, Ming Yu

“…ObjectiveThis study aims to develop a prediction model for invasive metastasis of primary liver cancer based on serum extracellular matrix metalloproteinase-inducing factor (CD147) and interleukin-6 (IL-6).MethodsBetween July 2022 and August 2024, 170 surgically treated primary hepatocellular carcinoma patients at our hospital were recruited. …”
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A phase separation-related gene signature for prognosis prediction and immunotherapy response evaluation in gastric cancer with targeted natural compound discovery by Yanjuan Jia, Yuanyuan Ma, Zhenhao Li, Wenze Zhang, Rukun Lu, Wanxia Wang, Chaojun Wei, Chunyan Wei, Yonghong Li, Xiaoling Gao, Tao Qu

“…Conclusions Our study developed a novel PS-related risk model that predicts GC outcomes, characterizes tumor immune microenvironment, evaluates immunotherapy response, and identifies targeting small molecules. …”
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Predicting China’s Energy Consumption and CO₂ Emissions by Employing a Novel Grey Model by Meixia Wang

“…The results show that the optimization method is reasonable. Third, compared with the traditional models GM, GMO, and ARIMA, the OGMW(1,1) provides better simulation and prediction accuracy, and new information can be prioritized more effectively. …”
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Evaluation of a Computed Tomography-based Technique for Predicting Atrial Fibrillation Recurrence Following Ablation Using an Adjusted Skeletal Muscle Index by Pingchuan Ma, Zhicheng Gao, Jiaqi Bao, Yilan Hu, Pengfei Sun, Qiqi Yan, Lifang Ye, Lihong Wang

“…Methods: This study included 641 patients with AF who underwent radiofrequency ablation. …”
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Construction and evaluation of an anxiety risk prediction model for the elderly (老年人焦虑风险预测模型的构建与评价) by ZHANG Jie (张洁), ZHU Xuehua (祝雪花)

“…Objective To construct a risk prediction model and evaluating its predictive forecasting performance to predict the occurrence of anxiety in older adults. …”
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Construction and evaluation of a predictive model for the degree of coronary artery occlusion based on adaptive weighted multi-modal fusion of traditional Chinese and western medic... by Jiyu ZHANG, Jiatuo XU, Liping TU, Hongyuan FU

“…Objective: To develop a non-invasive predictive model for coronary artery stenosis severity based on adaptive multi-modal integration of traditional Chinese and western medicine data. …”
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Myeloid response evaluated by noninvasive CT imaging predicts post-surgical survival and immune checkpoint therapy benefits in patients with hepatocellular carcinoma by Kangqiang Peng, Xiao Zhang, Xiao Zhang, Zhongliang Li, Yongchun Wang, Yongchun Wang, Hong-Wei Sun, Wei Zhao, Wei Zhao, Jielin Pan, Jielin Pan, Xiao-Yang Zhang, Xiaoling Wu, Xiangrong Yu, Xiangrong Yu, Chong Wu, Yulan Weng, Xiaowen Lin, Dingjie Liu, Dingjie Liu, Meixiao Zhan, Meixiao Zhan, Jing Xu, Limin Zheng, Limin Zheng, Yaojun Zhang, Ligong Lu, Ligong Lu

“…The prognostic performance of the Clinical-iMRS nomogram was better than that of a single parameter (p < 0.05), with a 1-, 3-, and 5-year C-index for RFS of 0.729, 0.709, and 0.713 in the training, test, and surgical resection cohorts, respectively. A high iMRS score predicted a higher proportion of objective response (vs. progressive disease or stable disease; odds ratio, 2.311; 95% CI, 1.144–4.672; p = 0.020; AUC, 0.718) in patients treated with anti-PD-1 and PD-L1.ConclusionsiMRS may provide a promising method for predicting local myeloid immune responses in HCC patients, inferring postsurgical prognosis, and evaluating benefits of immune checkpoint therapy.…”
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Collecting Performance Prediction for the Rubber Collector in Horizontal Wellbore Based on AutoML by Shaohua Li, Yang Li, Longlin Chen, Xianbin Wang, Weihang Kong

“…To objectively study the influencing factors of rubber collector performance in horizontal wellbores and identify parameter optimization directions, this paper introduces a modeling approach for rubber collectors in horizontal wellbores and develops a corresponding performance prediction method using AutoML(implemented with AutoGluon V1.2.0). …”
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