A CT-based radiomics model for predicting progression-free survival in patients with epithelial ovarian cancer by Yinping Leng, Jingjing Zhou, Wenjie Liu, Fengyuan Luo, Fei Peng, Lianggeng Gong

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Value of a diagnostic model based on composite inflammatory and nutritional indicators in predicting early colorectal cancer by LIU Xinyue, DING Xueli, YU Yanan, LIU Ailing, TIAN Zibin

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Stroma gene signature predicts responsiveness to chemotherapy in pancreatic ductal adenocarcinoma patient‐derived xenograft models by Alessia Anastasia, Laura Formenti, Paola Ostano, Lucia Minoli, Andrea Resovi, Lavinia Morosi, Claudia Fioravanti, Edoardo Micotti, Cristina Matteo, Eugenio Scanziani, Giovanna Chiorino, Raffaella Giavazzi, Carmen Ghilardi, Dorina Belotti

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Explainable, federated deep learning model predicts disease progression risk of cutaneous squamous cell carcinoma by Juan I. Pisula, Doris Helbig, Lucas Sancéré, Oana-Diana Persa, Corinna Bürger, Anne Fröhlich, Carina Lorenz, Sandra Bingmann, Dennis Niebel, Konstantin Drexler, Jennifer Landsberg, Roman Thomas, Katarzyna Bozek, Johannes Brägelmann

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Short-Term Prediction of Ship Heave Motion Using a PSO-Optimized CNN-LSTM Model by Guowei Li, Gang Tang, Jingyu Zhang, Qun Sun, Xiangjun Liu

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Predicting Running Vertical Ground Reaction Forces Using Neural Network Models Based on an IMU Sensor by Shangxiao Li, Jiahui Pan, Dongmei Wang, Shufang Yuan, Jin Yang, Weiya Hao

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Prediction of prognosis, efficacy of lung adenocarcinoma by machine learning model based on immune and metabolic related genes by Cong Xue, Yi-Zhi Dai, Gui-Long Li, Yi Zhang

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A new deep learning model for predicting IMRT dose distributions for lung cancer with dose masks by Xuezhen Feng, Xuezhen Feng, Mingqing Wang, Xinyan Lin, Xinyan Lin, Can Li, Can Li, Yuxi Pan, Guoping Zuo, Ruijie Yang

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Predicting Pharmacokinetics of Active Constituents in <i>Spatholobi caulis</i> by Using Physiologically Based Pharmacokinetic Models by Xiaoyan Liu, Ruihu Du, Tao Zhang, Yingzi Li, Ludi Li, Zheng Yang, Youbo Zhang, Qi Wang

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Classification of primary glomerulonephritis using machine learning models: a focus on IgA nephropathy prediction by Zhengbiao Hu, Shuangshan Bu, Kai Wang, Qianqian Cao, Huanhuan Zheng, Jie Yang, Shanshan Chen, Yuemeng Wu, Wenkai Ren, Chenlei He

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Predicting emotional responses in interactive art using Random Forests: a model grounded in enactive aesthetics by Xiaowei Chen, Xiaowei Chen, Zainuddin Ibrahim, Azlan Abdul Aziz

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Integrative machine learning model of RNA modifications predict prognosis and treatment response in patients with breast cancer by Tao Wang, Shu Wang, Zhuolin Li, Jie Xie, Qi Jia, Jing Hou

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A hypoxia‐related lncRNA model for prediction of head and neck squamous cell carcinoma prognosis by Junwei Xiang, Yaodong He, Yunshan Li, Kexuan Wu, Mengxiang Cheng, Yuanyin Wang, Ran Chen

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Evaluating mesoscale model predictions of diurnal speedup events in the Altamont Pass Wind Resource Area of California by R. S. Arthur, A. Rybchuk, T. W. Juliano, G. Rios, S. Wharton, J. K. Lundquist, J. K. Lundquist, J. D. Fast

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A pilot prospective study based on scanning OCT: the intraoperative vault model predicts postoperative vault by Zhongjun Tang, Yanze Yu, Jing Zhao, Yang Shen, Shengtao Liu, Xingtao Zhou

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Machine learning model for predicting tertiary lymphoid structures and treatment response in triple-negative breast cancer by Yidan Lin, Yushuai Yu, Qing Wang, Kaiyan Huang, Shukai Guo, Jie Zhang, Yihui He, Xin Yu, Jiwen Zhang, Fan Meng, Shicong Tang, Junhui Yuan, Chuangui Song

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Development and validation of an explainable machine learning prediction model of hemorrhagic transformation after intravenous thrombolysis in stroke by Yanan Lin, Yan Li, Yayin Luo, Jie Han

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Prediction Model for Determination of Indications for Laser or Surgical Treatment for Aggressive Posterior Retinopathy of Prematurity at the Manifestation Stage by A. V. Tereshhenko, I. G. Trifanenkova, Yu. A. Sidorova, M. S. Tereshhenkova, E. V. Erohina, S. V. Isaev

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Utilization of a Joint Point Regression Model for Predicting Mortality Rates of Common Cancers in Babol City by Pouyan Ebrahimi, Sara Khaleghi, Mohebat Vali, Sahar Delavari, Soraya Khafri, Mohsen Karami, Layla Shojaie, Hossein‐Ali Nikbakht

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A Novel Nomogram Model for Predicting the Risk of Hepatocellular Carcinoma in Patients with Chronic Hepatitis B Infection by Wu Y, Wang M, Zhang Z, Chen G, Zhang B

“…A web-based calculator was developed(https://nomogram-model-hcc.shinyapps.io/DynNomapp/).Conclusion: The novel nomogram model, which includes age, sex, liver cirrhosis, NLR, TBIL, AST, ALB, AFP, and HBV DNA as factors, precisely predicts the risk of HCC in patients with chronic hepatitis B(CHB) and outperforms the existing models.Keywords: HBV infection, HCC, neutrophil/platelet count ratio, prediction…”
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