Machine Learning Predicts 30‐Day Readmission and Mortality After Surgical Resection of Head and Neck Cancer by Daniel Fu, Aman M. Patel, Lucy Revercomb, Andrey Filimonov, Ghayoour S. Mir

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Predictability of clinical outcomes after external beam radiotherapy for hepatocellular carcinoma according to tumor marker dynamics. by Sunmin Park, Chai Hong Rim, Young Kul Jung, Hyung Joon Yim, Hwan Hoon Chung, Won Sup Yoon

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Data-driven prediction of critical diameter for deterministic lateral displacement devices: an integrated DPD-ML approach by Shuai Liu, Peng Zhang, Anbin Wang, Keke Tang, Shuo Chen, Chensen Lin

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Prediction of Selenium-Enriched Crop Zones in Xiaoyan Town Using Fuzzy Logic and Machine Learning Approaches by Jiacheng Li, Shuyun Xie, Wenbing Yang, Weihang Zhou, Emmanuel John M. Carranza, Weiji Wen, Hongtao Shi

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Multimodal deep learning for enhanced temperature prediction with uncertainty quantification in directed energy deposition (DED) process by Adrian Matias Chung Baek, Taehwan Kim, Minkyu Seong, Seungjae Lee, Hogyeong Kang, Eunju Park, Im Doo Jung, Namhun Kim

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Imaging-Based AI for Predicting Lymphovascular Space Invasion in Cervical Cancer: Systematic Review and Meta-Analysis by Lizhen She, Yunfeng Li, Hongyong Wang, Jun Zhang, Yuechen Zhao, Jie Cui, Ling Qiu

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A novel ubiquitination-related gene signature for overall survival prediction in patients with liver hepatocellular carcinoma by Xiuyun Chen, SenLin Li, Lixue Cao, Shaoxian Chen, Qiuxiong Lin, Shilong Zhong

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CT-based quantification of spatiotemporal heterogeneity for predicting response to neoadjuvant chemotherapy in locally advanced gastric cancer by Wenjun Hu, Liangjie Lin, Changjun Ma, Anliang Chen, Zhongbao Luo, Ziming Zhang, Ailian Liu

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A multi-biomarker machine learning approach for early prediction of interstitial lung disease in rheumatoid arthritis by Jiaojiao Xu, Wei Zhang, Weili Bai, Nannan Gai, Jing Li, Yunqi Bao

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Machine Learning for Identifying Damage and Predicting Properties in 3D-Printed PLA/Lygeum Spartum Biocomposites by Khalil Benabderazag, Moussa Guebailia, Zouheyr Belouadah, Lotfi Toubal, Salah Eddine Tachi

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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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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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The Brief Measure of Emotional Preoperative Stress (B-MEPS) as a new predictive tool for postoperative pain: A prospective observational cohort study. by Anelise Schifino Wolmeister, Carolina Lourenzon Schiavo, Kahio César Kuntz Nazário, Stela Maris de Jezus Castro, Andressa de Souza, Rafael Poli Caetani, Wolnei Caumo, Luciana Cadore Stefani

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DoNext: An Open-Access Measurement Dataset for Machine Learning-Driven 5G Mobile Network Analysis by Hendrik Schippers, Melina Geis, Stefan Bocker, Christian Wietfeld

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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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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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