Machine Learning-Based Diabetes Risk Prediction Using Associated Behavioral Features by Ayodeji O. J. Ibitoye, Joseph D. Akinyemi, Olufade F. W. Onifade

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An effective method for detecting the wheat freshness by integrating biophotonics and machine learning algorithm by Weiya Shi, Liang Chen

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Machine Learning-Based Normal White Blood Cell Multi-Classification Optimization by Taeyeon Gil, Sukjun Lee, Onseok Lee

“…Several studies have employed deep learning (DL) or machine learning (ML) methods; no significant difference in performance between the two methods has been demonstrated. …”
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Machine learning to identify environmental drivers of phytoplankton blooms in the Southern Baltic Sea by Maximilian Berthold, Pascal Nieters, Rahel Vortmeyer-Kley

Subjects: “…Scientific machine learning…”
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Spatio-temporal risk prediction of leptospirosis: A machine-learning-based approach by Rodrigue Govan, Romane Scherrer, Baptiste Fougeron, Christine Laporte-Magoni, Roman Thibeaux, Pierre Genthon, Philippe Fournier-Viger, Cyrille Goarant, Nazha Selmaoui-Folcher

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Recycled integrated circuit detection using reliability analysis and machine learning algorithms by Udaya Shankar Santhana Krishnan, Kalpana Palanisamy

“…In this work, three machine learning methods, namely K‐means clustering, back propagation neural network (BPNN) and support vector machines (SVMs), are used to detect the recycled IC aged for a shorter period (1 day) with minimum data size. …”
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Machine learning models and methods for solving optimization and forecasting problems of the work of seaports by M. N. Lukashevich, M. Y. Kovalyov

Subjects: “…machine learning…”
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Prediction of Proton Pressure in the Outer Part of the Inner Magnetosphere Using Machine Learning by S. Y. Li, E. A. Kronberg, C. G. Mouikis, H. Luo, Y. S. Ge, A. M. Du

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Investigation on the thermal characteristics of electronic system and prediction of chip temperature by machine learning by Fanyu Wang, Dongwei Wang, Qiang Deng, Hao Yan, Qi Chen, Yang Zhao

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Machine Learning Models of Acute Kidney Injury Prediction in Acute Pancreatitis Patients by Cheng Qu, Lin Gao, Xian-qiang Yu, Mei Wei, Guo-quan Fang, Jianing He, Long-xiang Cao, Lu Ke, Zhi-hui Tong, Wei-qin Li

“…Acute kidney injury (AKI) has long been recognized as a common and important complication of acute pancreatitis (AP). In the study, machine learning (ML) techniques were used to establish predictive models for AKI in AP patients during hospitalization. …”
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Exploring the Potential Imaging Biomarkers for Parkinson’s Disease Using Machine Learning Approach by Illia Mushta, Sulev Koks, Anton Popov, Oleksandr Lysenko

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Chemical Diversity of UK-Grown Tea Explored Using Metabolomics and Machine Learning by Amanda J. Lloyd, Alina Warren-Walker, Jasen Finch, Jo Harper, Kathryn Bennet, Alison Watson, Laura Lyons, Pilar Martinez Martin, Thomas Wilson, Manfred Beckmann

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Applying Data Analysis and Machine Learning Methods to Predict Permafrost Coast Erosion by Daria Bogatova, Stanislav Ogorodov

“…This study aims to establish a scientific and methodological basis for predicting shoreline positions using modern data analysis and machine learning techniques. The focus area is a 5 km section of the Ural coast along Baydaratskaya Bay in the Kara Sea. …”
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Mathematical Modeling of Properties and Structures of Crystals: From Quantum Approach to Machine Learning by Grzegorz Matyszczak, Christopher Jasiak, Gabriela Rusinkiewicz, Kinga Domian, Michał Brzozowski, Krzysztof Krawczyk

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Can AI/Machine Learning Make Physical Therapy Valuable in the Healthcare Marketplace? by Reuben Gobezie

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Predicting Sentiments in Spotify Comments: A Comparative Analysis of Machine Learning Models by Filipe Augusto Felix de Queiroz, Igor Barbosa Negreiros, Giovana de Souza, Débora Cordeiro de Sousa, Sílvio Fernando Alves Xavier Júnior

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Machine learning and public health policy evaluation: research dynamics and prospects for challenges by Zhengyin Li, Hui Zhou, Zhen Xu, Qingyang Ma

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Time Effort Prediction Of Agile Software Development Using Machine Learning Techniques by Muchamad Bachram Shidiq, Windu Gata, Sigit Kurniawan, Dedi Dwi Saputra, Supriadi Panggabean

“…For this reason, this research aims to predict the time effort of agile software development using Machine Learning techniques, namely the Decision Tree, Random Forest, Gradient Boosting, and AdaBoost algorithms, as well as the use of feature selection in the form of RRelieff and Principal Component Analysis (PCA) to improve prediction accuracy. …”
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A Machine-Learning-Based Classification Method for Meteorological Conditions of Ozone Pollution by Yang Cao, Xiaoli Zhao, Debin Su, Xiang Cheng, Hong Ren

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A System of Remote Patients’ Monitoring and Alerting Using the Machine Learning Technique by M. Dhinakaran, Khongdet Phasinam, Joel Alanya-Beltran, Kingshuk Srivastava, D. Vijendra Babu, Sitesh Kumar Singh

“…Machine learning has become an essential tool in daily life, or we can say it is a powerful tool in the majority of areas that we wish to optimize. …”
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