Prediction of the thermophysical properties of Ag-reduced graphene oxide-water/ethylene-glycol hybrid nanofluids using different machine learning methods by Huaguang Li, Ali B.M. Ali, Rasha Abed Hussein, Narinderjit Singh Sawaran Singh, Barno Abdullaeva, Zubair Ahmad, Soheil Salahshour, Mohammadreza Baghoolizadeh, Mostafa Pirmoradian

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Analysis of Possibilities to Automate Detection of Unscrupulous Microfinance Organizations based on Machine learning Methods by Yu. M. Beketnova

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Machine learning for predicting 5-year mortality risks: data from the ESSE-RF study in Primorsky Krai by V. A. Nevzorova, T. A. Brodskaya, K. I. Shakhgeldyan, B. I. Geltser, V. V. Kosterin, L. G. Priseko

Subjects: “…machine learning methods…”
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Predicting Ocean Current Temperature Off the East Coast of America with XGBoost and Random Forest Algorithms Using Rstudio by Lulut Alfaris, Anas Noor Firdaus, Ukta Indra Nyuswantoro, Ruben Cornelius Siagian, Aldi Cahya Muhammad, Rohana Hassan, Rodulfo T. Aunzo, Jr., Reza Ariefka

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Comparison of Lithuanian and Polish Consonant Phonemes Based on Acoustic Analysis – Preliminary Results by Gražina KORVEL, Olga KURASOVA, Bożena KOSTEK

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Verification of subclinical carotid atherosclerosis as part of risk stratification in overweight and obesity: the role of machine learning in the development of a diagnostic algori... by M. A. Druzhilov, T. Yu. Kuznetsova, D. V. Gavrilov, A. V. Gusev

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Identification of fungal diseases in strawberry by analysis of hyperspectral images using machine learning methods by A. F. Cheshkova

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Application of interpretable machine learning algorithms to predict macroangiopathy risk in Chinese patients with type 2 diabetes mellitus by Ningjie Zhang, Yan Wang, Hui Zhang, Huilong Fang, Xinyi Li, Zhifen Li, Zhenghang Huan, Zugui Zhang, Yongjun Wang, Wei Li, Zheng Gong

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Modeling Porosity Surface of 3D Selective Laser Melting Metal Materials by Matej Babič, Roman Šturm, Teofil-Florin Gălățanu, Ildikó-Renáta Száva, Ioan Száva

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MACHINE LEARNING BASED PREDICTION AND INSIGHTS OF DIABETES DISEASE: PIMA INDIAN AND FRANKFURT DATASETS by Mohammad Raquibul Hossain, Md. Jamal Hossain, Md. Mijanoor Rahman, Mohammad Manjur Alam

Subjects: “…machine learning methods…”
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COMPARISON OF DATASET OVERSAMPLING ALGORITHMS AND THEIR APPLICABILITY TO THE CATEGORIZATION PROBLEM by Denys Teslenko, Anna Sorokina, Artem Khovrat, Nural Huliiev, Valentyna Kyriy

Subjects: “…categorization; machine learning; methods of balancing; data generation methods; dataset; unbalanced datasets.…”
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Integrative analysis of gene expression and DNA methylation through one‐class logistic regression machine learning identifies stemness features in medulloblastoma by Hao Lian, Yi‐Peng Han, Yu‐Chao Zhang, Yang Zhao, Shan Yan, Qi‐Feng Li, Bao‐Cheng Wang, Jia‐Jia Wang, Wei Meng, Jian Yang, Qin‐Hua Wang, Wei‐Wei Mao, Jie Ma

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Machine learning in predicting immediate and long-term outcomes of myocardial revascularization: a systematic review by B. I. Geltser, V. Yu. Rublev, M. M. Tsivanyuk, K. I. Shakhgeldyan

Subjects: “…machine learning methods…”
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Robust-tuning machine learning algorithms for precise prediction of permeability impairment due to CaCO3 deposition by Mohammad Javad Khodabakhshi, Masoud Bijani, Masoud Hasani

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Role of necroptosis and immune infiltration in essential thrombocytosis by Guangming Li, Ying Guo, Yuanyuan Zhang

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Review of Spot Electricity Price Prediction Studies Based on Machine Learning Methods by JIA Heping, GUO Yuchen, MA Qianxin, YANG Zhenglin, ZHENG Yaxian, ZENG Dan, LIU Dunnan

Subjects: “…national unified electricity market|spot market|electricity price forecasting|machine learning methods…”
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Estimation of total Effort and Effort Elapsed in Each Step of Software Development Using Optimal Bayesian Belief Network by Fatemeh Zare Baghiabad, Hasan Khademi Zare, Mohammadsaber Fallahnezhad, Fazlollah Adibnia

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Modeling, Simulation, and Control of a Rotary Inverted Pendulum: A Reinforcement Learning-Based Control Approach by Ruben Hernandez, Ramon Garcia-Hernandez, Francisco Jurado

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Machine Learning-Based Damage Diagnosis in Floating Wind Turbines Using Vibration Signals: A Lab-Scale Study Under Different Wind Speeds and Directions by John S. Korolis, Dimitrios M. Bourdalos, John S. Sakellariou

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Examining Nasdaq Market Data and Presenting an Optimized Model by Extreme Gradient Boosting Regression and Artificial Bee Colony by Ali Ahmadpour

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