Machine learning-based anomaly detection and prediction in commercial aircraft using autonomous surveillance data. by Tian Xia, Lanju Zhou, Khalil Ahmad

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Ultrasound combined with serological markers for predicting neonatal necrotizing enterocolitis: a machine learning approach by Yi Yang, Shoulan Zhou, Xiaomin Liu, Yanhong Zhang, Liping Lin, Chenhan Zheng, Xiaohong Zhong

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ALSTNet: Autoencoder fused long‐ and short‐term time‐series network for the prediction of tunnel structure by Bowen Du, Haohan Liang, Yuhang Wang, Junchen Ye, Xuyan Tan, Weizhong Chen

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Integrating artificial intelligence with network evolution theory for community behavior prediction in dynamic complex systems by Yongyan Zhao, Jian Li

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HSoMLSDP: A Hybrid Swarm-Optimized Machine Learning Framework for Software Defect Prediction by Madhusmita Das, Biju R. Mohan, Ram Mohana Reddy Guddeti

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An Adaptive Spatio-Temporal Traffic Flow Prediction Using Self-Attention and Multi-Graph Networks by Basma Alsehaimi, Ohoud Alzamzami, Nahed Alowidi, Manar Ali

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Prediction of Flexural Ultimate Capacity for Reinforced UHPC Beams Using Ensemble Learning and SHAP Method by Zhe Zhang, Xuemei Zhou, Ping Zhu, Zhaochao Li, Yichuan Wang

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An artificial intelligence platform for predicting postoperative complications in metastatic spinal surgery: development and validation study by Weihao Jiang, Juan Zhang, Weiqing Shi, Xuyong Cao, Xiongwei Zhao, Bin Zhang, Haikuan Yu, Shengjie Wang, Yong Qin, Mingxing Lei, Yuncen Cao, Boyu Zhu, Yaosheng Liu

“…These variables were thus incorporated as key features in all the predictive models. Among the six machine learning models, the eXGBM model demonstrated the highest prediction accuracy, with an area under the curve (AUC) of 0.924 (95% CI: 0.884–0.965), outperforming the RF model (AUC = 0.892, 95% CI: 0.846–0.938) and the KNN model (AUC = 0.869, 95% CI: 0.818–0.920). …”
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Multimodal MRI radiomics based on habitat subregions of the tumor microenvironment for predicting risk stratification in glioblastoma. by Han Wang

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Machine-learning approach to atrial fibrillation prediction among individuals without prior cardiovascular diseases by Niklas Hammar, Javier Louro, Karin Modig, Shunsuke Murata, Mozhu Ding

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Value of multi-modal MRI in predicting the effect of high-intensity focused ultrasound for uterine fibroids by Si-Qi Tao, Li-Ye Shi, Xiao-Shan Chai, Xiao-Rui Yuan, Shi-Xiong Tang, Jun Zhang, Du-Jun Bian, Chun Fu

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A nomogram for predicting postpartum post-traumatic stress disorder: a prospective cohort study by Xiaoting Wang, Jiaxin Ren, Linping Kang, Jing Lu, Hongxia Wang

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Comparative Study on Total Organic Carbon Content Logging Prediction Method Based on Machine Learning by TANG Shengshou, YANG Bin, JIN Jiulong, LIU Hongrui, DAI Xingyu, PU Jincheng

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Measurement-Based Prediction of mmWave Channel Parameters Using Deep Learning and Point Cloud by Hang Mi, Bo Ai, Ruisi He, Anuraag Bodi, Raied Caromi, Jian Wang, Jelena Senic, Camillo Gentile, Yang Miao

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THGB: predicting ligand-receptor interactions by combining tree boosting and histogram-based gradient boosting by Liqian Zhou, Jiao Song, Zejun Li, Yingxi Hu, Wenyan Guo

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TraitBertGCN: Personality Trait Prediction Using BertGCN with Data Fusion Technique by Muhammad Waqas, Fengli Zhang, Asif Ali Laghari, Ahmad Almadhor, Filip Petrinec, Asif Iqbal, Mian Muhammad Yasir Khalil

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An evolutionary game theory-based machine learning framework for predicting mandatory lane change decision by Sixuan Xu, Mengyun Li, Wei Zhou, Jiyang Zhang, Chen Wang

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Integration of Hyperspectral Imaging and Deep Learning for Discrimination of Fumigated Lilies and Prediction of Quality Indicator Contents by Pengfei Zhang, Youyou Wang, Binbin Yan, Xiufu Wang, Zihua Zhang, Sheng Wang, Jian Yang

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A novel efferocytosis-related gene signature for predicting prognosis and therapeutic response in bladder cancer by Weitao Yu, Dongnuan Yao, Xueming Ma, Juanjuan Hou, Junqiang Tian

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Soot Mass Concentration Prediction at the GPF Inlet of GDI Engine Based on Machine Learning Methods by Zhiyuan Hu, Zeyu Liu, Jiayi Shen, Shimao Wang, Piqiang Tan

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