Prediction of outcomes following intravenous thrombolysis in patients with acute ischemic stroke using serum UCH-L1, S100β, and NSE: a multicenter prospective cohort study employin... by Ming-Ya Luo, Yang Qu, Peng Zhang, Reziya Abuduxukuer, Li-Juan Wang, Li-Chong Yang, Zhi-Guo Li, Xiao-Dong Liu, Ce Han, Dan Li, Wei-Jia Wang, Dian-Ping Lv, Ming Liu, Jian Gao, Jing Xu, Yongfei Jiang, Hai-Nan Chen, Fu-Jin Li, Li-Ming Sun, Qi-Dong Sun, Yingbin Qi, Si-Yin Sun, Yu Zhang, Zhen-Ni Guo, Yi Yang

“…Objectives: We aimed to assess the predictive value of serum brain injury biomarkers for 3-month outcomes in AIS patients treated with IVT, using an ML-based model. Design: A multicenter prospective cohort study was conducted, enrolling AIS patients treated with recombinant tissue plasminogen activator from 16 hospitals. …”
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KITE-DDI: A Knowledge Graph Integrated Transformer Model for Accurately Predicting Drug-Drug Interaction Events From Drug SMILES and Biomedical Knowledge Graph by Azwad Tamir, Jiann-Shiun Yuan

“…It is a common practice in modern medicine to prescribe multiple medications simultaneously to treat diseases. However, these medications could have adverse reactions between them, known as Drug-Drug Interactions (DDI), which have the potential to cause significant bodily injury and could even be fatal. …”
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Integrative analysis of epigenetic and transcriptional interrelations identifies histotype-specific biomarkers in early-stage ovarian carcinoma by Hugo Swenson, Ella Ittner, Lucas Werner, Elisabeth Werner Rönnerman, Claudia Mateoiu, Anikó Kovács, Pernilla Dahm-Kähler, Ghassan M. Saed, Szilárd Nemes, Per Karlsson, Toshima Z. Parris, Khalil Helou

“…Despite this heterogeneity, EOC is often treated as a homogenous disease, and reliable screening tests are lacking. …”
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A novel ensemble model for multi-temporal forest vegetation classification: integrating spectral-temporal features and topographic constraints by Rongfei Duan, Chunlin Huang, Peng Dou, Jinliang Hou, Ying Zhang

“…Spectral and temporal dimensions were jointly encoded to enhance feature representation, and an ensemble learning strategy was introduced to improve model robustness and adaptability. …”
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Classification of cervical cancer using Dense CapsNet with Seg-UNet and denoising autoencoders by Hui Yang, Walid Aydi, Nisreen Innab, Mohamed E. Ghoneim, Massimiliano Ferrara

“…Cervical cancer classification using machine learning (ML) and deep learning (DL) has been extensively studied to enhance the conventional diagnostic process. …”
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Challenges in AI-driven multi-omics data analysis for Oncology: Addressing dimensionality, sparsity, transparency and ethical considerations by Maryem Ouhmouk, Shakuntala Baichoo, Mounia Abik

“…We also discuss how well these methods consider explainability, interpretability, and ethical aspects in developing solutions that treat private medical and sensitive information.From the 32 studies, we can divide deep learning-based multi-omics integration methods into two types: non-generative and generative models. …”
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Endoscopic middle ear surgery: First steps in a third level hospital by Fabian Alzate Amaya, Liliana Invencio Da Costa, Anselmo Padin Seara, Jose Eugenio Estrada Gromaz

“…The purpose of this study is to describe patients diagnosed in our center with otologic surgical pathology who were treated through an endoscopicc approach. Methods:Retrospective cohort study of patients undergoing endoscopic ear surgery during the period from January 2015 to March 2018. …”
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Automated Detection of Schizophrenia Based on Retinal Measures and Neurological Soft Signs: Applications of Interpretable Classification Methods and the Choquet Integral Aggregatio... by Pawel Krukow, Steven M. Silverstein, Pawel Karczmarek, Adam Domagala, Adam Kiersztyn, Malgorzata Plechawska-Wojcik, Maria Garcia Gadanon, Kamil Jonak

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Stable phytoplankton community compositions in Lake Mead (Nevada-Arizona, USA) during two decades of severe drought by Charlotte van der Nagel, Deena Hannoun, Todd Tietjen

“…Additionally, we evaluated machine learning models for predicting changes in phytoplankton community structures. …”
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Dual-radiomics based on SHapley additive explanations for predicting hematologic toxicity in concurrent chemoradiotherapy patients by Luqiao Chen, Zhipeng He, Qianxi Ni, Qionghui Zhou, Xizi Long, Wenbin Yan, Qian Sui, Jiheng Liu

“…Methods Clinical information, planning CT images, and dose distribution files from 205 patients with advanced cervical cancer treated with CCRT were retrospectively collected. …”
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Assessing experiences of racism among Black and White patients in the emergency department by Anish K. Agarwal, Charlotte Sagan, Rachel Gonzales, Sally Nijim, Raina M. Merchant, David A. Asch, Eugenia C. South

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Development and validation of a prognostic prediction model for elderly gastric cancer patients based on oxidative stress biochemical markers by Xing-Qi Zhang, Ze-Ning Huang, Ju Wu, Chang-Yue Zheng, Xiao-Dong Liu, Ying-Qi Huang, Qi-Yue Chen, Ping Li, Jian-Wei Xie, Chao-Hui Zheng, Jian-Xian Lin, Yan-Bing Zhou, Chang-Ming Huang

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Uncertainty quantification in multi-parametric MRI-based meningioma radiotherapy target segmentation by Lana Wang, Zhenyu Yang, Zhenyu Yang, Dominic LaBella, Zachary Reitman, John Ginn, Jingtong Zhao, Justus Adamson, Kyle Lafata, Kyle Lafata, Kyle Lafata, Evan Calabrese, John Kirkpatrick, Chunhao Wang

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A data-driven approach utilizing machine learning (ML) and geographical information system (GIS)-based time series analysis with data augmentation for water quality assessment in M... by Abhijeet Das

“…In conclusion, this work showed that the water was potentially hazardous to health of the consumers at some investigated locations and highlighted the need to treat industrial and municipal wastewater. Therefore, this innovative research recommends integrating these modelling approaches due to their consistent and reliable results, which can reduce both the time and cost of analysis and be applied locally and globally using similar methodologies. …”
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Neural networks in oncourology by M. P. Korchagin, A. V. Govorov, A. O. Vasilyev, I. O. Gritskov, D. Yu. Pushkar

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Accuracy of ChatGPT-3.5, ChatGPT-4o, Copilot, Gemini, Claude, and Perplexity in advising on lumbosacral radicular pain against clinical practice guidelines: cross-sectional study by Giacomo Rossettini, Giacomo Rossettini, Silvia Bargeri, Chad Cook, Chad Cook, Chad Cook, Stefania Guida, Alvisa Palese, Lia Rodeghiero, Paolo Pillastrini, Paolo Pillastrini, Andrea Turolla, Andrea Turolla, Greta Castellini, Silvia Gianola

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In Silico Exploration of Novel EGFR Kinase Mutant-Selective Inhibitors Using a Hybrid Computational Approach by Md Ali Asif Noor, Md Mazedul Haq, Md Arifur Rahman Chowdhury, Hilal Tayara, HyunJoo Shim, Kil To Chong

“…Targeting epidermal growth factor receptor (EGFR) mutants is a promising strategy for treating non-small cell lung cancer (NSCLC). This study focused on the computational identification and characterization of potential EGFR mutant-selective inhibitors using pharmacophore design and validation by deep learning, virtual screening, ADMET (Absorption, distribution, metabolism, excretion and toxicity), and molecular docking-dynamics simulations. …”
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應用智慧型家教系統於國小學童閱讀策略 教學之學習歷程研究 A Study on the Learning Process of Applying an Autotutoring System to Teach Reading Strategies to Elementary School Children... by 陳茹玲 Ju-Ling Chen, 曾厚強 Hou-Chiang Tseng, 連啟舜 Chi-Shun Lien, 蔡旻穎 Min-Ying Tsai, 宋曜廷 Yao-Ting Sung

“…Learning process analysis used a one-way ANOVA, treating reading ability as the independent variable, pre-test background knowledge as a covariate, and learning time and paths as dependent variables. …”
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تعليميّة النّحو الوظيفيّ في ضوء المقاربة النّصيّة وأثرُها في تنمية الفهم القرائيّ لدى متعلمي صعوبات التّعلم... by Ali Belbahi, Sihem Laib

“…Therefore, it is essential to reconsider the way of treating the educational text in order to achieve the objectives, compatible skills and requirements of the emerging development in the field of language teaching. …”
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On Risk Assessment for Out-of-Distribution Detection by Anton Vasiliuk

“…This paper challenges the conventional approach treating of out-of-distribution (OOD) risk as uniform and aimed at reducing OOD risk on average. …”
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