Evaluating the impact of ESICM 2023 guidelines and the new global definition of ARDS on clinical outcomes: insights from MIMIC-IV cohort data by Duanhong Song, Qingquan Chen, Shangbin Huang, Shengxun Qiu, Zeshun Chen, Yuanhang Cai, Yifu Zeng, Xiaoyang Chen, Yixiang Zhang

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Comparing the results from a Swedish pregnancy cohort using data from three automated placental growth factor immunoassay platforms intended for first‐trimester preeclampsia predic... by Ylva Carlsson, Anna Sandström, Lina Bergman, Peter Conner, Stefan Hansson, Marius Kublickas, Uzay Görmüş, Peter Lindgren, Göran Oleröd, Anna‐Karin Wikström, Anders Larsson

“…Prediction models for preeclampsia often include circulating concentrations of placental growth factor (PlGF); however, the models are usually limited to a specific PlGF method of analysis. …”
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Evaluation of the Idle time of Single-Chain and Double-Chain Overhead Power Lines of 6–10 kV by Methods of Queuing Theory by Basmanov V.G., Kholmanskikh V.M.

“…The signifi-cance of the results obtained consists in that a simple engineering method is proposed to evalu-ate the availability factor of the overhead power line according to the reliability indicators of its main elements, which allows predicting the idle time of the overhead line for the upcoming cal-endar year of its operation. …”
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Large-scale evaluation of bacteriological-based method and qPCR performance for Brucellosis diagnosis in livestock using Bayesian latent class analysis by Giovanna Fusco, Alessandro Bellato, Lorena Cardillo, Agata Campione, Michela Di Roberto, Anna Cerrone, Francesca Bove, Roberta Pellicanò, Maria Ottaiano, Marco Esposito, Antonio Limone, Anna Rita Attili, Esterina De Carlo

“…Bacteriological culture demonstrated a higher Positive Predictive Value (PPV) than qPCR in both buffaloes and cattle, whereas the Negative Predictive Value (NPV) of the two methods did not differ significantly. …”
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Evaluation of a real-time optoelectronic method for the detection of cervical intraepithelial neoplasia and cervical cancer in patients with different transformation zone types by Fengyi Xiao, Long Sui

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Research on GRU-LSTM-Based Early Warning Method for Electric Vehicle Lithium-Ion Battery Voltage Fault Classification by Liang Zhang, Qizhi Wu, Longfei Wang, Ling Lyu, Linru Jiang, Yu Shi

“…Battery cell voltage is an important evaluation index for electric vehicle condition estimation and one of the main monitoring parameters of the battery management system, and accurate voltage prediction is crucial for electric vehicle battery failure warning. …”
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Comparative Evaluation of Ensemble Machine Learning Models for Methane Production from Anaerobic Digestion by Dorijan Radočaj, Mladen Jurišić

“…A total of six individual machine learning methods and five ensemble constructions were evaluated per dataset, whose prediction accuracy was assessed using a robust 10-fold cross-validation in 100 repetitions. …”
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Water quality evaluation in Liaoning Province large reservoirs: a new method integrating random forest-TOPSIS and Monte Carlo simulation by Chong Zhang, Mo Chen, Yi Wang

“…Validation of the model demonstrated a predictive accuracy rate exceeding 83.87%, outperforming other assessment methods such as the analytic hierarchy process, criteria importance through intercriteria correlation, the evidential weighting method, and the COV method. …”
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A Prediction Method for Flow-Stop Time in Deep-Water Volatile Oilfields: A Case Study of Akpo Oilfield in Niger Delta Basin by Botao Kang, Pengcheng Liu, Chenxi Li, Yiyi Sun, Peng Xiao, Jiawei Tang

“…A prediction method for the wellhead pressure was further established, and the flow-stop time of single well can be accurately predicted. …”
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VenusMutHub: A systematic evaluation of protein mutation effect predictors on small-scale experimental data by Liang Zhang, Hua Pang, Chenghao Zhang, Song Li, Yang Tan, Fan Jiang, Mingchen Li, Yuanxi Yu, Ziyi Zhou, Banghao Wu, Bingxin Zhou, Hao Liu, Pan Tan, Liang Hong

“…This benchmark provides practical guidance for selecting appropriate prediction methods in protein engineering applications where accurate prediction of specific functional properties is crucial.…”
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Development and evaluation of a machine learning model for post-surgical acute kidney injury in active infective endocarditis by XinPei Liu, SanXi Ai, RuiMing Yu, ChaoJi Zhang, Qi Miao

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Prediction of Weld Geometry in Laser Overlap Welding of Low-Carbon Galvanized Steel by Kamel Oussaid, Narges Omidi, Abderrazak El Ouafi, Noureddine Barka

“…Traditional finite element method (FEM)-based models provide reliable predictions but are computationally expensive and impractical for real-time applications. …”
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Fuzzy evaluation and explainable machine learning for diagnosis of rheumatic and autoimmune diseases by Mohammed Fadhil Mahdi, Arezoo Jahani, Dhafar Hamed Abd

“…To select the optimal model, we apply fuzzy decision by opinion score method (FDOSM). The FDOSM process involves assessments from three domain experts to ensure a robust and well-rounded evaluation. …”
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Modeling the therapeutic dynamics of acupuncture and moxibustion: a systems biology approach to treatment optimization by Quan Gan, Qi-Wei Ge, Chuanxia Liu, Zhaoman Zhong, Jiaying Wu, Lei Shi, Jin Xu, Chen Li

“…This study introduces a comprehensive framework for dynamic modeling, visual representation, and quantitative evaluation of AMT systems. By offering a systematic and predictive approach to AMT analysis, the proposed method not only enhances understanding of treatment mechanisms but also contributes to the standardization of clinical practice.…”
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Mixed mode fracture: numerical evaluation and experimental validation using PMMA specimens by Sérgio Alexandre Gonçalves Pereira, Sérgio M.O. Tavares, Paulo M.S.T. de Castro

“…The extended finite element method (XFEM) is also used to predict the crack trajectory under different loading conditions. …”
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The Effect of Resampling Techniques on Model Performance Classification of Maternal Health Risks by Nia Mauliza, Aisha Shakila Iedwan, Yoga Pristyanto, Anggit Dwi Hartanto, Arif Nur Rohman

“…This research aimed to improve prediction accuracy in the classification of pregnant women's diseases through the application of various resampling methods. …”
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Longwall panel width design with prediction of the corresponding maximum induced ground surface subsidence by Fariborz Matinpour, Abbas Majdi

“…Then, the paper continues to present two more new analytical methods for a suitable longwall panel width design and subsequently to predict the corresponding maximum induced ground surface subsidence. …”
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Research Progress on Ambient Visual Information Analysis and Perception Measurement Methods for Motion Vision by Haipeng ZHU, Yuhang KONG, (JPN) OHNO Ryuzo

“…By integrating objective physical environment analysis with subjective perception evaluation, the research proposes a unified framework to explore the mechanisms linking built environments with spatial cognition, and predicts future research directions.MethodsThis research employs a comprehensive review methodology to examine the mechanisms of dynamic visual perception in urban public spaces. …”
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Evaluating the impact of machine learning models on adult major depressive disorder using conventional treatment strategies: a systematic review approach by Nishant Yadav, Anamika Gulati, Varun Gulati, Prashant Yadav

“…However, methodology heterogeneity, varied sample sizes, and lack of external validation of these models limit their clinical use. Methods A comprehensive systematic review of 30 studies employing ML models for MDD treatment response prediction was conducted. …”
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Evaluating Ecological Vulnerability and Its Driving Mechanisms in the Dongting Lake Region from a Multi-Method Integrated Perspective: Based on Geodetector and Explainable Machine... by Fuchao Li, Tian Nan, Huang Zhang, Kun Luo, Kui Xiang, Yi Peng

“…The results indicate that: ① ecological vulnerability increased progressively from the core wetlands and riparian corridors to the transitional zones in the surrounding hills and mountains; ② a significant spatial clustering of ecological vulnerability was observed, with a Moran’s I index of 0.78; ③ Geodetector analysis identified the interaction between NPP (<i>q</i> = 0.329) and precipitation (PRE, <i>q</i> = 0.268) as the dominant factor (<i>q</i> = 0.50) influencing spatial variation of EVI; ④ the Random Forest model achieved the best classification performance (AUC = 0.954, <i>F</i>1 score = 0.78), and SHAP analysis showed that NPP and PRE made the most significant contributions to model predictions. This study proposes a multi-method integrated decision support framework for assessing ecological vulnerability in lake wetland ecosystems.…”
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