Machine learning analysis of emerging risk factors for early-onset hypertension in the Tlalpan 2020 cohort by Mireya Martínez-García, Guadalupe O. Gutiérrez-Esparza, Guadalupe O. Gutiérrez-Esparza, Manlio F. Márquez, Manlio F. Márquez, Luis M. Amezcua-Guerra, Enrique Hernández-Lemus, Enrique Hernández-Lemus

Subjects: “…machine learning models…”
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Sleep Posture Detection via Embedded Machine Learning on a Reduced Set of Pressure Sensors by Giacomo Peruzzi, Alessandra Galli, Giada Giorgi, Alessandro Pozzebon

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Solar energy prediction through machine learning models: A comparative analysis of regressor algorithms. by Huu Nam Nguyen, Quoc Thanh Tran, Canh Tung Ngo, Duc Dam Nguyen, Van Quan Tran

“…In this study, 5 machine learning models were used including: Gradient Boosting Regressor (GB), XGB Regressor (XGBoost), K-neighbors Regressor (KNN), LGBM Regressor (LightGBM), and CatBoost Regressor (CatBoost). …”
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Machine Learning Classifiers and Data Synthesis Techniques to Tackle with Highly Imbalanced COVID-19 Data by Avaz Naghipour, Mohammad Reza Abbaszadeh Bavil Soflaei, mostafa ghader-zefrehei

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Lung cancer Prediction and Classification based on Correlation Selection method Using Machine Learning Techniques by Dakhaz Mustafa Abdullah, Adnan Mohsin Abdulazeez, Amira Bibo Sallow

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Prediction of delirium occurrence using machine learning in acute stroke patients in intensive care unit by Hyungjun Kim, Hyungjun Kim, Min Kim, Da Young Kim, Dong Gi Seo, Ji Man Hong, Ji Man Hong, Dukyong Yoon, Dukyong Yoon

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A machine learning model the prediction of athlete engagement based on cohesion, passion and mental toughness by Xin Zhang, Zhikang Lin, Song Gu

Subjects: “…Machine learning…”
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Machine learning-assisted prediction of durability behavior in pultruded fiber-reinforced polymeric (PFRP) composites by Ammar A. Alshannaq, Mohammad F. Tamimi, Muath I. Abu Qamar

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A Comprehensive Machine Learning Approach for COVID-19 Target Discovery in the Small-Molecule Metabolome by Md. Shaheenur Islam Sumon, Md Sakib Abrar Hossain, Haya Al-Sulaiti, Hadi M. Yassine, Muhammad E. H. Chowdhury

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Estimation of minimum miscible pressure in carbon dioxide gas injection using machine learning methods by Ali Akbari, Ali Ranjbar, Yousef Kazemzadeh, Fatemeh Mohammadinia, Amirjavad Borhani

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Comparison between traditional logistic regression and machine learning for predicting mortality in adult sepsis patients by Hongsheng Wu, Biling Liao, Tengfei Ji, Keqiang Ma, Yumei Luo, Shengmin Zhang

Subjects: “…machine learning…”
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Retracted: Development of Microbiology Plantation-Based Multimodal Segmentation for Smart Garden Using Machine Learning by Advances in Materials Science and Engineering

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Sorghum yield prediction based on remote sensing and machine learning in conflict affected South Sudan by John Karongo, Joseph Ivivi Mwaniki, John Ndiritu, Victor Mokaya

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Machine learning-based forecasting of ground surface settlement induced by metro shield tunneling construction by Qiankun Wang, Chuxiong Shen, Chao Tang, Zeng Guo, Fangqi Wu, Wenyi Yang

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Retracted: Optimal Scheduling Model of WDM/OTN Network Transmission Line Based on Machine Learning by Journal of Control Science and Engineering

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Leveraging machine learning and rule extraction for enhanced transparency in emergency department length of stay prediction by Waqar A. Sulaiman, Charithea Stylianides, Andria Nikolaou, Andria Nikolaou, Zinonas Antoniou, Ioannis Constantinou, Lakis Palazis, Anna Vavlitou, Theodoros Kyprianou, Theodoros Kyprianou, Efthyvoulos Kyriacou, Antonis Kakas, Antonis Kakas, Marios S. Pattichis, Andreas S. Panayides, Constantinos S. Pattichis, Constantinos S. Pattichis

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AI-Driven Mental Health Surveillance: Identifying Suicidal Ideation Through Machine Learning Techniques by Hesham Allam, Chris Davison, Faisal Kalota, Edward Lazaros, David Hua

Subjects: “…machine learning…”
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Machine Learning-based Prediction of HBV-related Hepatocellular Carcinoma and Detection of Key Candidate Biomarkers by Zeynep KUCUKAKCALI, Sami AKBULUT, Cemil COLAK

“…Objective: This study aimed to classify open-access gene expression data of patients with hepatitis B virus-related hepatocellular carcinoma (HBV + HCC) and chronic HBV without HCC (HBV alone) using the XGBoost method, one of the machine learning methods, and reveal important genes that may cause HCC. …”
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PUPIL DIAMETER AND MACHINE LEARNING FOR DEPRESSION DETECTION: A COMPARATIVE STUDY WITH DEEP LEARNING MODELS by Islam MOHAMED, Mohamed EL-WAKAD, Khaled ABBAS, Mohamed ABOAMER, Nader A. Rahman MOHAMED

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Decision-making in clinical diagnostic for brain tumor detection based on advanced machine ‎learning algorithm‎ by Huang Tangsen, Yin Xiangdong, Jiang Ensong

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