Machine Learning–Based Prediction of Early Complications Following Surgery for Intestinal Obstruction: Multicenter Retrospective Study by Pinjie Huang, Jirong Yang, Dizhou Zhao, Taojia Ran, Yuheng Luo, Dong Yang, Xueqin Zheng, Shaoli Zhou, Chaojin Chen

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TSTA-GCN: trend spatio-temporal traffic flow prediction using adaptive graph convolution network by Xinlu Zong, Jiawei Guo, Fucai Liu, Fan Yu

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Lifetime prediction of epoxy coating using convolutional neural networks and post processing image recognition methods by Fandi Meng, Yufan Chen, Jianning Chi, Huan Wang, Fuhui Wang, Li Liu

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Circulating metabolic biomarkers predict incident sepsis: a large-scale population study in the UK Biobank by Hao Bai, Yihui Li, Miaomiao Fan, Mingmin Pang, Yanan Li, Shaohua Zhao, Tingyu Meng, Hao Chen, Ming Lu, Hao Wang

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Predicting grade II-IV bone marrow suppression in patients with cervical cancer based on radiomics and dosiomics by Yanchun Tang, Yanchun Tang, Yaru Pang, Jingyi Tang, Jingyi Tang, Xinchen Sun, Xinchen Sun, Peipei Wang, Jinkai Li

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StructureNet: Physics-Informed Hybridized Deep Learning Framework for Protein–Ligand Binding Affinity Prediction by Arjun Kaneriya, Madhav Samudrala, Harrish Ganesh, James Moran, Somanath Dandibhotla, Sivanesan Dakshanamurthy

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Explainable AI for Chronic Kidney Disease Prediction in Medical IoT: Integrating GANs and Few-Shot Learning by Nermeen Gamal Rezk, Samah Alshathri, Amged Sayed, Ezz El-Din Hemdan

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Prediction of breast cancer risk among women of the Mariana Islands: the BRISK retrospective case–control study by Lynne R Wilkens, Yurii B Shvetsov, Kami K White, Marie Chong, Arielle Buyum, Grazyna Badowski, Rachael T Leon Guerrero, Rachel Novotny

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Nonsuicidal self-injury prediction with pain-processing neural circuits using interpretable graph neural network by Sichu Wu, Yuan Xue, Yaming Hang, Ya Xie, Pei Zhang, Minlu Liang, Yuan Zhong, Chun Wang

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A Multi-Task Spatiotemporal Graph Neural Network for Transient Stability and State Prediction in Power Systems by Shuaibo Wang, Xinyuan Xiang, Jie Zhang, Zhuohang Liang, Shufang Li, Peilin Zhong, Jie Zeng, Chenguang Wang

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NSA-CHG: An Intelligent Prediction Framework for Real-Time TBM Parameter Optimization in Complex Geological Conditions by Youliang Chen, Wencan Guan, Rafig Azzam, Siyu Chen

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SolarGAN for Meso-Level Solar Radiation Prediction at the Urban Scale: A Case Study in Boston by Yijun Lu, Xinru Li, Siyuan Wu, Yuankai Wang, Waishan Qiu, Da Chen, Yifan Li

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Predicting treatment response to ketamine in treatment-resistant depression using auditory mismatch negativity: Study protocol. by Josh Martin, Fatemeh Gholamali Nezhad, Alice Rueda, Gyu Hee Lee, Colleen E Charlton, Milad Soltanzadeh, Karim S Ladha, Sridhar Krishnan, Andreea O Diaconescu, Venkat Bhat

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What Is My Plaza for? Implementing a Machine Learning Strategy for Public Events Prediction in the Urban Square by Jumana Hamdani, Pablo Antuña Molina, Lucía Leva Fuentes, Hesham Shawqy, Gabriella Rossi, David Andrés León

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The application of artificial intelligence techniques in predicting game outcomes of professional basketball league: A systematic review. by Chuxuan Li, Hao Zhang, Yuan Zhang, Jing Shen, Ruopeng An

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Optimizing Voice Sample Quantity and Recording Settings for the Prediction of Type 2 Diabetes Mellitus: Retrospective Study by Atousa Assadi, Jessica Oreskovic, Jaycee Kaufman, Yan Fossat

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Prediction of testicular histology in azoospermia patients through deep learning-enabled two-dimensional grayscale ultrasound by Jia-Ying Hu, Zhen-Zhe Lin, Li Ding, Zhi-Xing Zhang, Wan-Ling Huang, Sha-Sha Huang, Bin Li, Xiao-Yan Xie, Ming-De Lu, Chun-Hua Deng, Hao-Tian Lin, Yong Gao, Zhu Wang

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Efficient Deep Learning Job Allocation in Cloud Systems by Predicting Resource Consumptions including GPU and CPU by Abuda Chad Ferrino, Tae Young Choe

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Dynamicasome—a molecular dynamics-guided and AI-driven pathogenicity prediction catalogue for all genetic mutations by Naeyma N. Islam, Mathew A. Coban, Jessica M. Fuller, Caleb Weber, Rohit Chitale, Benjamin Jussila, Trisha J. Brock, Cui Tao, Thomas R. Caulfield

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Predicting the number density of heavy seed massive black holes due to an intense Lyman-Werner field by Hannah O'Brennan, John A. Regan, John Brennan, Joe McCaffrey, John H. Wise, Eli Visbal, Alessandro Trinca, Michael L. Norman

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