Identification and Evaluation of Lipocalin-2 in Sepsis-Associated Encephalopathy via Machine Learning Approaches by Hu J, Chen Z, Wang J, Xu A, Sun J, Xiao W, Yang M

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Potential Metabolic Markers in the Tongue Coating of Chronic Gastritis Patients for Distinguishing Between Cold Dampness Pattern and Damp Heat Pattern in Traditional Chinese Medici... by Yuan S, Zhang R, Zhu Z, Zhou X, Zhang H, Li X, Hao Y

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Machine Learning Methods for Predicting Cardiovascular Diseases: A Comparative Analysis by Aiym B. Temirbayeva, Arshyn Altybay

“…The primary research question is to identify which algorithm demonstrates the best predictive performance for heart disease diagnosis. …”
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Predicting the time to get back to work using statistical models and machine learning approaches by George Bouliotis, M. Underwood, R. Froud

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Maximum Likelihood Decoder for Variable Length Codes by Syed Misbahuddin, Mohammed Talal Simsim

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Analyzing the severity of distracted driving crashes on horizontal curves of rural highways: A hybrid approach of boosting-based ensemble machine learning and discrete choice metho... by Morteza Safari, Meysam Effati, Mahyar Arabani

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Investigating the Association Between Mean Arterial Pressure on 28-Day Mortality Risk in Patients With Sepsis: Retrospective Cohort Study Based on the MIMIC-IV Database by Qimin Chen, Wei Li, Ying Wang, Xianjun Chen, Dehua He, Ming Liu, Jia Yuan, Chuan Xiao, Qing Li, Lu Chen, Feng Shen

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Integrating near-infrared hyperspectral imaging with machine learning and feature selection: Detecting adulteration of extra-virgin olive oil with lower-grade olive oils and hazeln... by Derick Malavi, Katleen Raes, Sam Van Haute

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Machine Learning and Medical Data: Predicting ICU Mortality and Re-admission Risks by Runia Roy, Ulya Bayram

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Streamlining Thoracic Radiotherapy Quality assurance: One-Class Classification for Automated OAR Contour Assessment by Yihao Zhao BSc, Cuiyun Yuan MSc, Ying Liang PhD, Yang Li MSc, Chunxia Li MSc, Man Zhao MSc, Jun Hu PhD, Ningze Zhong Bsc, Wei Liu PhD, Chenbin Liu PhD

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Utilizing artificial intelligence for the detection of hemarthrosis in hemophilia using point-of-care ultrasonography by Pascal N. Tyrrell, María Teresa Alvarez-Román, Nihal Bakeer, Brigitte Brand-Staufer, Victor Jiménez-Yuste, Susan Kras, Carlo Martinoli, Mauro Mendez, Azusa Nagao, Margareth Ozelo, Janaina B.S. Ricciardi, Marek Zak, Johannes Roth

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Predicting regional tau accumulation with machine learning‐based tau‐PET and advanced radiomics by Saima Rathore, Ixavier A. Higgins, Jian Wang, Ian A. Kennedy, Leonardo Iaccarino, Samantha C. Burnham, Michael J. Pontecorvo, Sergey Shcherbinin

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Blood Vessel Segmentation and Classification of Diabetic Retinopathy with Machine Learning-Based Ensemble Model by Cihan Akyel, Bünyamin Ciylan

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Machine Learning Detection of Melting Layers From Radar Observations by Yan Xie, Fraser King, Claire Pettersen, Mark Flanner

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A Novel Minimization Method for Sensor Deployment Via Heuristic 2-Sat Solution by Waleed Ahmed, Ali Muhammad Ali Rushdi

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Optimizing Cardiovascular Risk Assessment with a Soft Voting Classifier Ensemble by Ammar Oad, Zulfikar Ahmed Maher, Imtiaz Hussain Koondhar, Karishima Kumari, Hammad Bacha

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Classifying the Emotional Polarity of Digital Communications Using Large Language Models by Vincent Qin

“… Large Language Models (LLMs) employ deep learning algorithms to generalize patterns in data. Applying these LLMs to classification tasks can reduce the required labor and time. …”
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Energy Risk Analysis With Dynamic Amplitude Estimation and Piecewise Approximate Quantum Compiling by Kumar Ghosh, Kavitha Yogaraj, Gabriele Agliardi, Piergiacomo Sabino, Fernandez-Campoamor Marina, Bernabe-Moreno Juan, Giorgio Cortiana, Omar Shehab, Corey O'Meara

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Implementation of the methodology for calculation of the three-phase equilibrium of hydrocarbons and the aqueous phase by Oleg Aksenov, Mikhail Kozlov, Eduard Usov, Dmitry Taylakov, Nikita Kayurov, Alexander Cheremisin

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Alleviating the quantum Big-M problem by Edoardo Alessandroni, Sergi Ramos-Calderer, Ingo Roth, Emiliano Traversi, Leandro Aolita

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