LINGUISTIC ANALYSIS FOR THE BELARUSIAN CORPUS WITH THE APPLICATION OF NATURAL LANGUAGE PROCESSING AND MACHINE LEARNING TECHNIQUES by Yu. S. Hetsevich, I. V. Reentovich

“…The natural language processing of Belarusian corpus with the help of developed algorithm using machine learning was carried out. The precision of developed models of machine learning has been 80–90 %. …”
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Machine learning-driven identification of critical gene programs and key transcription factors in migraine by Lei Zhang, Yujie Li, Yunhao Xu, Wei Wang, Guangyu Guo

“…This study applies machine learning techniques to explore region-specific gene expression profiles and identify critical gene programs and transcription factors linked to migraine pathogenesis. …”
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Review on the Application of Remote Sensing Data and Machine Learning to the Estimation of Anthropogenic Heat Emissions by Lingyun Feng, Danyang Ma, Min Xie, Mengzhu Xi

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PegasosQSVM: A Quantum Machine Learning Approach for Accurate Fake News Detection by Mehdi Khalil, Chi Zhang, Zhiwei Ye, Peng Zhang

“…The rapid spread of fake news on social media poses a significant threat to modern societies. Traditional machine learning approaches have limitations in handling the ever-increasing volume and complexity of data. …”
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Machine Learning-Based Models for Prediction of Critical Illness at Community, Paramedic, and Hospital Stages by Sijin Lee, Hyun Ji Park, Jumi Hwang, Sung Woo Lee, Kap Su Han, Won Young Kim, Jinwoo Jeong, Hyunggoo Kang, Armi Kim, Chulung Lee, Su Jin Kim

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Handling Imbalance Classification Virtual Screening Big Data Using Machine Learning Algorithms by Sahar K. Hussin, Salah M. Abdelmageid, Adel Alkhalil, Yasser M. Omar, Mahmoud I. Marie, Rabie A. Ramadan

“…Virtual screening is the most critical process in drug discovery, and it relies on machine learning to facilitate the screening process. It enables the discovery of molecules that bind to a specific protein to form a drug. …”
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Predicting mechanical properties of bainitic rail steels based on microstructure digitalization and machine learning by L.Q. Bai, Z.Y. Ding, J.L. Wang, Z.J. Xie, Z.N. Yang, C.J. Shang

Subjects: “…Machine learning…”
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Improving machine learning predictions to estimate fishing effort using vessel's tracking data by J. Samarão, A. Moreno, M.B. Gaspar, M.M. Rufino

“…These approaches should be applied in all works using machine learning to produce fishing effort maps.…”
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Leveraging survival analysis and machine learning for accurate prediction of breast cancer recurrence and metastasis by Shahd M. Noman, Youssef M. Fadel, Mayar T. Henedak, Nada A. Attia, Malak Essam, Sarah Elmaasarawii, Fayrouz A. Fouad, Esraa G. Eltasawi, Walid Al-Atabany

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Dilated cardiomyopathy signature metabolic marker screening: Machine learning and multi-omics analysis by Xiao-Lei Li, Aibibanmu Aizezi, Yan-Peng Li, Yan-Hong Li, Fen Liu, Qian Zhao, Xiang Ma, Dilare Adi, Yi-Tong Ma

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Author Correction: An interpretable and transparent machine learning framework for appendicitis detection in pediatric patients by Krishnaraj Chadaga, Varada Khanna, Srikanth Prabhu, Niranjana Sampathila, Rajagopala Chadaga, Shashikiran Umakanth, Devadas Bhat, K. S. Swathi, Radhika Kamath

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Comparative study on deep and machine learning approaches for predicting wind pressures on tall buildings by Mosbeh R. Kaloop, Abidhan Bardhan, Pijush Samui, Jong Wan Hu, Mohamed Elsharawy

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APPLICATION OF MACHINE LEARNING ALGORITHMS TO EVALUATE THE UCI DATABASE IN THE CLASSIFICATION OF AUTISM SPECTRUM DISORDERS by Phạm Quang Thuận, Nguyễn Đình Thuân

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Advancing UAV Communications: A Comprehensive Survey of Cutting-Edge Machine Learning Techniques by Chenrui Sun, Gianluca Fontanesi, Berk Canberk, Amirhossein Mohajerzadeh, Symeon Chatzinotas, David Grace, Hamed Ahmadi

“…This paper provides a comprehensive overview of the evolution of Machine Learning (ML), from traditional to advanced, in its application and integration into unmanned aerial vehicle (UAV) communication frameworks and practical applications. …”
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A Comparative Study Evaluated the Performance of Two-class Classification Algorithms in Machine Learning by Shilan Abdullah Hassan, Maha Sabah Saeed

Subjects: “…Machine Learning…”
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A systematic review of machine learning applications in predicting opioid associated adverse events by Carlos R. Ramírez Medina, Jose Benitez-Aurioles, David A. Jenkins, Meghna Jani

“…Abstract Machine learning has increasingly been applied to predict opioid-related harms due to its ability to handle complex interactions and generating actionable predictions. …”
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Integrating Machine Learning for Predictive Maintenance on Resource-Constrained PLCs: A Feasibility Study by Riccardo Mennilli, Luigi Mazza, Andrea Mura

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Design and optimization of distributed energy management system based on edge computing and machine learning by Nan Feng, Conglin Ran

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Predict the Maximum Dry Density of Soil Based on Individual and Hybrid Methods of Machine Learning by Ghanshyam Tejani, Behnam Sadaghat, Sumit Kumar

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Glaucoma detection and staging from visual field images using machine learning techniques. by Nahida Akter, Jack Gordon, Sherry Li, Mikki Poon, Stuart Perry, John Fletcher, Thomas Chan, Andrew White, Maitreyee Roy

“…The DL model results were compared with a machine learning (ML) classifier trained on conventional VF parameters.…”
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