CD34 evaluation of microvasculature in lung adenocarcinoma and its microvascular density predicts postoperative tumor recurrence by Zijian Qiu, Jiaji Wu, Guanchao Pang, Xia Xu, Jun Lin, Pingli Wang

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Deep Learning Framework Using Transformer Networks for Multi Building Energy Consumption Prediction in Smart Cities by Samuel Moveh, Emmanuel Alejandro Merchán-Cruz, Maher Abuhussain, Yakubu Aminu Dodo, Saleh Alhumaid, Ali Hussain Alhamami

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Predicting treatment response in individuals with major depressive disorder using structural MRI-based similarity features by Sutao Song, Songling Wang, Jingjing Gao, Lingkai Zhu, Wenxin Zhang, Yan Wang, Donglin Wang, Danning Zhang, Kangcheng Wang

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Predicted Spatial Patterns of Suitable Habitats for <i>Troides aeacus</i> Under Different Climate Scenarios by Biyu Liu, Xinqi Deng, Zhiqian Liu, Xinju Wei, Honghua Zhang, Danping Xu, Zhihang Zhuo

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Predicting Predisposition to Tropical Diseases in Female Adults Using Risk Factors: An Explainable-Machine Learning Approach by Kingsley Friday Attai, Constance Amannah, Moses Ekpenyong, Said Baadel, Okure Obot, Daniel Asuquo, Ekerette Attai, Faith-Valentine Uzoka, Emem Dan, Christie Akwaowo, Faith-Michael Uzoka

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Experimental Study on Heat Transfer Performance of FKS-TPMS Heat Sink Designs and Time Series Prediction by Mahsa Hajialibabaei, Mohamad Ziad Saghir

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A lightweight triple-modal fusion network for progressive mild cognitive impairment prediction in Alzheimer's disease by Xiangyu Shen, Xiangyang Hu, Renfeng Zhang, Yunzhan Fu, Jiamin Xu, Degang Lyu, Hongbiao Xie, Hongbiao Xie, Deen Shi, Changsheng Shi, Lisi Li, Yuantong Gao

“…Although multimodal neuroimaging and clinical data provide complementary information, existing fusion models often face challenges such as high computational complexity and limited interpretability.MethodsTo address these limitations, we introduce TriLightNet, an innovative lightweight triple-modal fusion network designed to integrate structural MRI, functional PET, and clinical tabular data for predicting MCI-to-AD conversion. …”
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GT-NMR: a novel graph transformer-based approach for accurate prediction of NMR chemical shifts by Haochen Chen, Tao Liang, Kai Tan, Anan Wu, Xin Lu

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Remaining Useful Life Prediction for Rolling Bearings Based on TCN–Transformer Networks Using Vibration Signals by Xiaochao Jin, Yaping Ji, Shiteng Li, Kailang Lv, Jianzheng Xu, Haonan Jiang, Shengnan Fu

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Identification and validation of LDHA and SLC16A1 for predicting prognosis and diagnosis in lower-grade glioma by Jingyi Huang, Qishun Wang, Zhijun Li, Xuning Huang, Wen Wang, Jiao Liu

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Prediction of the Methane Yield From Extensively Managed, Flower‐Rich Fen Grassland Based on NIRS Data by M. Wendt, S. Nandke, P. Scharschmidt, M. Thielicke, J. Ahlborn, M. Heiermann, F. Eulenstein

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deep-Sep: a deep learning-based method for fast and accurate prediction of selenoprotein genes in bacteria by Yao Xiao, Yan Zhang

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Predicting postoperative motor outcomes in the surgical management of Rolandic focal cortical dysplasia: the role of glucose metabolism by Weiyuan Luo, Bowen Yang, Xiaobin Zhao, Baotian Zhao, Chao Zhang, Xiu Wang, Jiajie Mo, Xiangzhi Lu, Zhong Zheng, Xiaoqiu Shao, Jianguo Zhang, Kai Zhang, Wenhan Hu

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355 Validation of an artificial intelligence Algorithm for predicting diagnosis-related groups in a community health system by Angela Muhanga, King Jason, Xsolis Mueller, Jennifer L. Sanger, Julie M. Bartlett, Brian N. Manz, James W. Spiten, Matthew J. Overgaard, Shauna M. Wang Hanyin

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Post-surgical fall risk prediction: a machine learning approach for spine and lower extremity procedures by Ya-Huei Chen, Xing-Yu Luo, Chia-Hui Chang, Chen-Tsung Kuo, Sou-Jen Shih, Mei-Yu Chang, Mei-Rong Weng, I-Chieh Chen, Ying-Lin Hsu, Ying-Lin Hsu, Jia-Lang Xu

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Spatial features of tumor-infiltrating lymphocytes in primary lesions of lung adenocarcinoma predict lymph node metastasis by Huibo Zhang, Ming Luo, Junwei Feng, Juan Tan, Yan Jiang, Dmitrij Frishman, Yang Liu

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Cluster Analysis of Clinical Remission and Relapse Patterns in Chronic Urticaria: Results from the PREDICT-CU Study by Maria-Magdalena Balp, Irina Pivneva, Andrii Danyliv, Kathleen Chen, Tom Cornwall, Jimmy Royer, James Signorovitch, Dhaval Patil, Ravneet K. Kohli, Thomas Severin, Weily Soong, Alexander M. Marsland

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A Bayesian Network Approach to Predicting Severity Status in Nuclear Reactor Accidents with Resilience to Missing Data by Kaiyu Li, Ling Chen, Xinxin Cai, Cai Xu, Yuncheng Lu, Shengfeng Luo, Wenlin Wang, Lizhi Jiang, Guohua Wu

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Fibroblast growth factor receptor risk signature predicts patient prognosis and immunotherapy resistance in colorectal cancer by Xiaofang Li, Zhiling Pan, Zhiling Pan, Tiankuo Luan, Qian Xiao, Liuying Li, Qianxue Wu, Guoqing Yao, Xiang Zhang, Daqiang Song

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Cell death-related signature genes: risk-predictive biomarkers and potential therapeutic targets in severe sepsis by Yanan Li, Yuqiu Tan, Zengwen Ma, Zengwen Ma, Weiwei Qian, Weiwei Qian

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