Research Progress on Adhesion Mechanism and Testing Methods of Emulsified Asphalt–Aggregate Interface by Hao-Yue Huang, Xiao Han, Sen Han, Xiao Ma, Jia Guo, Yao Huang

“…There are challenges in predicting and controlling the adhesion performance under complex environments, as well as important opportunities for developing advanced characterization techniques and multiscale simulation methods.…”
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Using the particle finite element method for predicting edge-cracking in complex phase high-strength steel sheets by Sandin Olle, Larour Patrick, Rodríguez Juan Manuel, Kajberg Jörgen, Casellas Daniel

“…The presented PFEM framework predicts optimal cutting conditions for specific AHSS grades by evaluating edge characteristics, such as roll-over, burnish, fracture, and burr, across various clearances. …”
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Improving measures of context in process evaluations: development and use of the Context Tracker tool by Joanna Busza, Fortunate Machingura, Cedomir Vuckovic

“…Methods We present a method to help structure measures of context in process evaluations and describe its use in two very different settings. …”
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An improved method for predicting the permeability of Chang 7 shale oil reservoirs based on lithology and hydraulic flow units by Heting Gao, Yanze Sun, Hui Zhao, Fei Zhou, Weichao Tian, Zhigang Wen, Yunpeng Fan, Xiaoyu Chen

“…Abstract Accurate permeability characterization is essential for evaluating shale oil reservoirs quality. Chang 7 shale oil reservoirs, with diverse lithologies, low porosities and permeabilities, complex pore structures, and strong heterogeneity, pose challenges for traditional permeability prediction methods. …”
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Prediction on Permeability Coefficient of Continuously Graded Coarse-Grained Soils: A Data-Driven Machine Learning Method by Jinhua Wang, Haibin Ding, Lingxiao Guan, Yulin Wang

“…Compared to a traditional empirical model (R² = 0.9031), BPNN improved prediction accuracy by 10.13%, demonstrating the advantage of data-driven methods for evaluating CGS permeability.…”
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Evaluation of placental growth factor, Vitamin D, and systemic inflammatory index as predictive biomarkers for preeclampsia severity: a retrospective cohort study by Xiaoyan Han, Hua Yang

“…Abstract Aim Our study aimed to evaluate the predictive value of Placental growth factor (PlGF), Vitamin D, and systemic inflammatory index for assessing preeclampsia risk and severity. …”
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RETROSPECTIVE EVALUATION OF ASA CLASSIFICATION’S PREDICTIVE ABILITY OF POSTOPERATIVE COMPLICATIONS IN PATIENTS ADMITTED TO INTENSIVE CARE UNIT AFTER MAJOR ABDOMINOPELVIC SURGERY by Emre Sertaç Bingül, Ayşe Hızal, Başar Erdivanlı, Hızır Kazdal

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Evaluation of Torque Teno Virus DNA Load as a Predictive Biomarker in Kidney Transplant Recipients Converted from Calcineurin Inhibitors to Belatacept by Lara Cabezas, Aurelie Truffot, Raphaele Germi, Mathilde Bugnazet, Paolo Malvezzi, Manon Gnesotto, Lionel Rostaing, Thomas Jouve, Johan Noble

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Machine learning prediction models for mortality risk in sepsis-associated acute kidney injury: evaluating early versus late CRRT initiation by Chuanren Zhuang, Ruomeng Hu, Ke Li, Zhengshuang Liu, Songjie Bai, Sheng Zhang, Xuehuan Wen

“…Multiple machine learning models were developed and evaluated to predict patient prognosis, with Shapley Additive exPlanations (SHAP) analysis identifying key prognostic factors.ResultsAfter propensity score matching, late CRRT initiation was associated with improved survival probability, but led to increased hospital and ICU stays. …”
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Improvement in low-homology template-based modeling by employing a model evaluation method with focus on topology. by Wentao Dai, Tingrui Song, Xuan Wang, Xiaoyang Jin, Lizong Deng, Aiping Wu, Taijiao Jiang

“…To improve the performance of TBM methods for such targets, a novel model evaluation method was developed here, and named MEFTop. …”
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Comparative Discrimination of Life’s Simple 7, Life’s Essential 8, and Life’s Crucial 9: Evaluating the impact of added complexity on mortality prediction by Xu Zhu, Iokfai Cheang, Yiyang Fu, Sitong Chen, Gengmin Liang, Huaxin Yuan, Ling Zhu, Haifeng Zhang, Xinli Li

“…This study aimed to assess whether the additional components in LE8 and LC9 enhance mortality prediction compared to LS7. Methods Data from 22,382 participants in the NHANES 2005–2018 were analyzed. …”
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Predictive Factors of Length of Stay in Intensive Care Unit after Coronary Artery Bypass Graft Surgery based on Machine Learning Methods by Alireza Jafarkhani, Behzad Imani, Soheila Saeedi, Amir Shams

“… Introduction: Coronary artery bypass grafting (CABG) surgery requires an extended length of stay (LOS) in the intensive care unit (ICU). This study aimed to predict the factors affecting LOS in the ICU after CABG surgery using machine learning methods. …”
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Fatigue property evaluation of 7075/6061 aluminum alloy TIG welded overlap joints by LIAO Xiangyun, WANG Ruijie, LIU Guoshou, ZHAO Pinglin, CHANG Yaguang, WANG Zhongde

“…Both the point method and the line method within the critical distance method can predict hot spot stress, but the point method yields more precise results than the line method.…”
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Comparative Efficacy of MultiModal AI Methods in Screening for Major Depressive Disorder: Machine Learning Model Development Predictive Pilot Study by Donghao Chen, Pengfei Wang, Xiaolong Zhang, Runqi Qiao, Nanxi Li, Xiaodong Zhang, Honggang Zhang, Gang Wang

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Probabilistic-Based Forecasting Method For Time Series Datasets by Abdullatif Baba

“…The predicted states that are determined by using our method converge rapidly towards the real values while a classical linear model exhibits a large amount of divergence if used alone here. …”
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Automatic method to predict visual pleasantness and unpleasantness of streetscapes and identify key microscale components for improving pedestrian environments by Meesung Lee, Byungjoo Choi, Sungjoo Hwang

“…This study advances urban evaluation by developing an automatic method to predict streetscape quality and analyze microscale components. …”
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The prediction method for ground surface settlement of pipe jacking tunnels based on a spatiotemporal transfer learning network by Hairong Huang, Lian Yuan, Jian Chen, Shixia Zhang

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Beyond Global Metrics: The U-Smile Method for Explainable, Interpretable, and Transparent Variable Selection in Risk Prediction Models by Katarzyna B. Kubiak, Agata Konieczna, Anna Tyranska-Fobke, Barbara Więckowska

“…To address this limitation, we developed the U-smile method, a residual-based, post hoc evaluation approach for assessing prediction improvements and worsening separately for events and non-events. …”
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An AI method to predict pregnancy loss by extracting biological indicators from embryo ultrasound recordings in early pregnancy by Lijue Liu, Yuan Zang, Huimu Zheng, Siya Li, Yu Song, Xue Feng, Xiyuan Zhang, Yaoxu Li, Lulu Cao, Guanglin Zhou, Tingting Dong, Qi Huang, Teng Pan, Jinhai Deng, Danling Cheng

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Machine Learning Method for TOC Prediction: Taking Wufeng and Longmaxi Shales in the Sichuan Basin, Southwest China as an Example by Jia Rong, Zongyuan Zheng, Xiaorong Luo, Chao Li, Yuping Li, Xiangfeng Wei, Quanchao Wei, Guangchun Yu, Likuan Zhang, Yuhong Lei

“…The total organic carbon content (TOC) is a core indicator for shale gas reservoir evaluations. Machine learning-based models can quickly and accurately predict TOC, which is of great significance for the production of shale gas. …”
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