Machine learning algorithms for prediction of cerebrospinal fluid leakage after posterior surgery for thoracic ossification of the ligamentum flavum by Ruizhou Guo, Ben Liu, Yunqi Wu, Yilu Zhang, Xiyang Wang, Dingyu Jiang, Zheng Liu

“…A SMOTE-enhanced, isotonic-calibrated SVM provides accurate and reliable CSFL risk estimation in TOLF patients and is freely available as an online tool ( https://github.com/DebtVC2022/CSFL_predict ). The model supports preoperative risk stratification, patient counselling, and peri-operative management, yet requires prospective, multicentre validation to establish broad clinical utility.…”
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Intelligent Prediction of the Horizontal Deformation During the Excavation Process Based on Particle Swarm Optimisation and Support Vector Machine by Yu Zhang, Chen Zhang, Zhiduo Zhu, Liu Yang, Hao Tang

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Enhanced Lung Cancer Prediction via Integrated Multi‐Space Feature Adaptation, Collaborative Alignment and Disentanglement Learning by Abigail Kawama, Ronald Waweru Mwangi, Lawrence Nderu

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Relevance-Based Reconstruction Using an Empirical Mode Decomposition Informer for Lithium-Ion Battery Surface-Temperature Prediction by Chao Li, Yigang Kong, Changjiang Wang, Xueliang Wang, Min Wang, Yulong Wang

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Nomogram establishment for gastrointestinal bleeding prediction in ICU patients with traumatic brain injury based on the MIMIC-IV database by Ziming Huang, Hengfa Ge, Ying Sun

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Data-Driven Customer Retention Strategies in E-Commerce: A Fuzzy Z-Number Approach by Siyin Hu, An Chen

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Cascaded Machine Learning of Soil Moisture and Salinity Prediction in Estuarine Wetlands Based on In Situ Internet of Things Monitoring by Jie Song, Yujun Yi

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FEPP: Advancing Software Risk Prediction in Requirements Engineering Through Innovative Rule Extraction and Multi-Class Integration by Muhammad Binsawad, Bilal Khan

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Development of an in vitro model to study muscle maladaptation to overtraining by Giuseppe Sirago, Clément Lanfranchi, Justin Carrard, Vincent Gremeaux, Nadège Zanou, Nicolas Place

“…Nature Communications, 12(1), 7219. https://doi.org/10.1038/s41467-021-27422-1 …”
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Predictive control of musculotendon loads across fast and slow-twitch muscles in a simulated system with parallel actuation by Mahdi Nabipour, Gregory S. Sawicki, Massimo Sartori

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Predicting hypoglycemia risk after gastrointestinal surgery in type 2 diabetes mellitus: a retrospective cohort study by Huilan Yao, Shijin Yuan, Hongying Pan, Sisi Hong, Chen Huang, Linfang Zhao, Hongdi Yuan, Lei Mei, Yinghong Zheng, Xiaolong Liu, Weina Lu

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Predicting 30-day in-hospital mortality in ICU asthma patients: a retrospective machine learning study with external validation by Yuanshuo Ge, Guangdong Wang, Tingting Liu, Wenwen Ji, Jiaolin Sun, Yaxin Zhang

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SaeGraphDTI: drug–target interaction prediction based on sequence attribute extraction and graph neural network by Qiaosheng Zhang, Zhenyu Sun, Zhaoman Zhong, Huihui Yang, Yalong Wei, Junjie Xu

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Optimal path selection and secured data transmission in underwater acoustic sensor networks: LSTM-based energy prediction. by Sathish Kaveripakam, Ravikumar Chinthaginjala

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Stress–Strain Prediction for Steam-Cured Steel Slag Fine Aggregate Concrete Based on Machine Learning Algorithms by Chuanshang Wang, Di Hu, Qiang Jin

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A Metaheuristic-Trained Wavelet Neural Network for Predicting of Soil Liquefaction Based on the Standard Penetration Test Results by Ali Reza Ghanizadeh, Ahmad Aziminejad

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Enhanced Alzheimer’s Disease Prediction Through Integration of Protein-Protein Interaction Data and Meta-Learning by Hansa J. Thattil, M. N. Arunkumar, Francis Antony

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Machine learning algorithms to predict heart failure with preserved ejection fraction among patients with premature myocardial infarction by Jing-xian Wang, Chang-ping Li, Zhuang Cui, Yan Liang, Yu-hang Wang, Yu Zhou, Yin Liu, Jing Gao, Jing Gao, Jing Gao, Jing Gao

“…The final model included ten variables, which were Brain natriuretic peptide (BNP) > 100pg/ml, SYNTAX Score > 14.5, Age, Monocyte to Lymphocyte Ratio (MLR) > 0.3, Hematocrit (HCT) < 45%, Heart rate (HR) > 75 bpm, Body Mass Index (BMI) ≥ 24 kg/m2, C-reactive Protein to Lymphocyte Ratio (CLR) > 2.83, Hypertension and Fibrinogen (Fg) > 4 g/L.ConclusionsThe explainable prediction model established based on the XGBoost algorithm can accurately predict the risk of in-hospital HFpEF in PMI patients and is available at https://hfpefpmi.shinyapps.io/apppredict/. …”
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Dynamic SOFA component scores-based deep learning for short to long-term mortality prediction in sepsis survivors by Juan Wei, Feihong Lin, Tian Jin, Qian Yao, Sheng Wang, Di Feng, Xin Lv, Wen He

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Prediction method of oil-water interface between injection and production wells in fault-controlled fractured-cavity reservoirs by WANG Yuanzheng, CAO Renyi, JIA Pin

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