Evaluation of the SAMe-TT2R2 score to predict the quality of anticoagulation control in patients after mitral valve replacement by Yilin Li, Yang Gao, Qiuming Hu, Xu Meng, Shubin Li

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Machine learning prediction of extended length of stay following endoscopic decompression for lumbar spinal stenosis: A retrospective cohort study by Fuqiang Tan, Xiaobin Li, Chaoyang Qu, Xin Shu, Xu Peng

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Artificial intelligence-driven translational medicine: a machine learning framework for predicting disease outcomes and optimizing patient-centric care by Laith Abualigah, Saleh Ali Alomari, Mohammad H. Almomani, Raed Abu Zitar, Kashif Saleem, Hazem Migdady, Vaclav Snasel, Aseel Smerat, Absalom E. Ezugwu

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Serum anion gap and its interaction with diabetes in predicting mortality among critically ill patients with non-traumatic intracerebral hemorrhage by Yong Wen, Xiaorui Xie, Keli He

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Alterations in Suitable Cultivation Area for <i>Scutellaria baicalensis</i> under Future Climatic Scenarios in China: Geodetector-Based Prediction by Yuanyuan Yin, Jing’ai Wang, Wensheng Zhang, Benfeng Yin, Jixia Huang, Zijing Zhang

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Effects of Subsetting by Parent Materials on Prediction of Soil Organic Matter Content in a Hilly Area Using Vis-NIR Spectroscopy. by Shengxiang Xu, Xuezheng Shi, Meiyan Wang, Yongcun Zhao

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Identifying Key Factors for Predicting the Age at Peak Height Velocity in Preadolescent Team Sports Athletes Using Explainable Machine Learning by Nikolaos-Orestis Retzepis, Alexandra Avloniti, Christos Kokkotis, Maria Protopapa, Theodoros Stampoulis, Anastasia Gkachtsou, Dimitris Pantazis, Dimitris Balampanos, Ilias Smilios, Athanasios Chatzinikolaou

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Robust Gas Demand Prediction Using Deep Neural Networks: A Data-Driven Approach to Forecasting Under Regulatory Constraints by Kostiantyn Pavlov, Olena Pavlova, Tomasz Wołowiec, Svitlana Slobodian, Andriy Tymchyshak, Tetiana Vlasenko

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Machine Learning For Risk Prediction After Heart Failure Emergency Department Visit or Hospital Admission Using Administrative Health Data. by Nowell M Fine, Sunil V Kalmady, Weijie Sun, Russ Greiner, Jonathan G Howlett, James A White, Finlay A McAlister, Justin A Ezekowitz, Padma Kaul

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Prediction of the Binding to the Nuclear Factor NF-Kappa-B by Constituents from <i>Teucrium polium</i> L. Essential Oil by Renilson Castro de Barros, Renato Araújo da Costa, Nesrine Guenane, Boulanouar Bakchiche, Farouk Benaceur, Omer Elkiran, Suelem Daniella Pinho Farias, Vanessa Regina Silva Mota, Maria Fani Dolabela

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Predicting high anger intensity using ecological momentary assessment and wearable-derived physiological data in a trauma-affected sample by Olivia Metcalf, Karen E. Lamb, David Forbes, Meaghan L. O’Donnell, Tianchen Qian, Tracey Varker, Sean Cowlishaw, Sophie Zaloumis

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Multiparametric radiomics signature for predicting molecular genotypes in adult-type diffuse gliomas utilizing 18F-FET PET/MRI by Jie Bai, Bixiao Cui, Fengqi Li, Xin Han, Hongwei Yang, Jie Lu

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Circulating miR-4454 as a potential biomarker for the diagnosis of T2DM and the prediction value of comorbidity and complications in T2DM by Song Yang, Mei Wang, Qin Deng

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Is higher resolution always better? A comparison of open-access DEMs for optimized slope unit delineation and regional landslide prediction by M. Ahmed, G. Titti, S. Trevisani, L. Borgatti, M. Francioni

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Evaluating clinician acceptability of the prototype CanRisk tool for predicting risk of breast and ovarian cancer: A multi-methods study. by Stephanie Archer, Chantal Babb de Villiers, Fiona Scheibl, Tim Carver, Simon Hartley, Andrew Lee, Alex P Cunningham, Douglas F Easton, Jennifer G McIntosh, Jon Emery, Marc Tischkowitz, Antonis C Antoniou, Fiona M Walter

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deepTFBS: Improving within‐ and Cross‐Species Prediction of Transcription Factor Binding Using Deep Multi‐Task and Transfer Learning by Jingjing Zhai, Yuzhou Zhang, Chujun Zhang, Xiaotong Yin, Minggui Song, Chenglong Tang, Pengjun Ding, Zenglin Li, Chuang Ma

“…In this study, deepTFBS, a comprehensive deep learning (DL) framework that builds a robust DNA language model of TF binding grammar for accurately predicting TFBSs within and across plant species is presented. …”
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A nomogram based on quantitative MR signal intensity predicts early response to combined systemic treatment in patients with hepatocellular carcinoma by Ran Tao, Haohao Lu, Xiangjun Dong, Qian Qian Ren, Hongjie Fan, Zhaoming Tang, Xiangwen Xia

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Peripheral blood markers predict prognosis and irAEs of stage IV driver gene-negative lung adenocarcinoma treated with ICIs by Yu Li, Lei Cao, Lei Liu, Yawen Ding, Feng Cao

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Preoperative MRI and CA19-9 for predicting occult lymph node metastasis in small pancreatic ductal adenocarcinoma (≤ 2 cm) by Qiying Tang, Lei Li, Zhiwei Pan, Jianbo Li, Xiaolan Huang, Mengsu Zeng, Haitao Sun, Jianjun Zhou

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LRMAHpan: a novel tool for multi-allelic HLA presentation prediction using Resnet-based and LSTM-based neural networks by Xue Mi, Shaohao Li, Zheng Ye, Zhu Dai, Bo Ding, Bo Sun, Yang Shen, Yang Shen, Zhongdang Xiao, Zhongdang Xiao

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