Identifying Ring Galaxies in DESI Legacy Imaging Surveys Using Machine Learning Methods by Aina Zhang, Xiaoming Kong, Bowen Liu, Nan Li, Yude Bu, Zhenping Yi, Meng Liu

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Human limits in machine learning: prediction of potato yield and disease using soil microbiome data by Rosa Aghdam, Xudong Tang, Shan Shan, Richard Lankau, Claudia Solís-Lemus

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Predictive Analytics for Sucker Rod Pump Failures in Kazakhstani Oil Wells Using Machine Learning by Laura Utemissova, Timur Merembayev, Bakbergen Bekbau, Sagyn Omirbekov

“…The authors applied machine learning approaches to an imbalanced dataset. …”
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Machine learning in dentistry and oral surgery: charting the course with bibliometric insights by Shuangwei Liu, Yuquan Hao, Shijie Zhu, Liyao Wan, Zhe Yi, Zhichang Zhang

Subjects: “…Machine learning…”
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Analyzing and Predicting the Agronomic Effectiveness of Fertilizers Derived from Food Waste Using Data-Driven Models by Ksawery Kuligowski, Quoc Ba Tran, Chinh Chien Nguyen, Piotr Kaczyński, Izabela Konkol, Lesław Świerczek, Adam Cenian, Xuan Cuong Nguyen

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An analytics-driven model for identifying autism spectrum disorder using eye tracking by Deblina Mazumder Setu

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A comprehensive review of predictive analytics models for mental illness using machine learning algorithms by Md. Monirul Islam, Shahriar Hassan, Sharmin Akter, Ferdaus Anam Jibon, Md. Sahidullah

“…This study reviews the machine learning models, algorithms, and applications for the early detection of mental disease, particularly emphasizing the data modalities. …”
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Do Machine Learning and Business Analytics Approaches Answer the Question of ‘Will Your Kickstarter Project be Successful? by Murat Kılınç, Can Aydın, Çiğdem Tarhan

“…Within this scope, a business intelligence model that works on the web has been developed by combining business analytics and machine learning methods. The data used for business analytics has been brought to a state that can provide inferences through visualization, reporting and query processes. …”
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Brain functional connectivity analysis of fMRI-based Alzheimer's disease data by Maitha S. Alarjani, Badar A. Almarri

“…These features are then used as inputs for an Extreme Learning Machine (ELM) model to classify AD stages. …”
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Experimental assessment and data-driven hybrid machine learning quantification with parametric optimization of compressive strength of ceramic waste concrete by Mihir Mishra, Md. Habibur Rahman Sobuz, Md. Kawsarul Islam Kabbo, M Jameel, Turki S. Alahmari, Naim Ahmad, Md. Munir Hayet Khan

“…This study aims to develop hybrid machine learning (ML) models for ceramic waste-based concrete (CWC) to predict its compressive strength (CS) and analyze the mix parameters that significantly impact its strength. …”
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A Machine Learning Approach to Explore and Predict Student Motivation Types by Hafsa Al Ansari, Rasha Shakir Abdulwahhab Al Jassim, Rupert Ward

“…The proposed framework employs multi-source data and evaluates three machine learning techniques: Multinomial Regression, Support Vector Machine, and XGBoost. …”
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Leveraging machine learning in nursing: innovations, challenges, and ethical insights by Sophie So Wan Yip, Sheng Ning, Niki Yan Ki Wong, Jeffrey Chan, Kei Shing Ng, Bernadette Oi Ting Kwok, Robert L. Anders, Simon Ching Lam

“…Aim/objectiveThis review aims to provide a comprehensive analysis of the integration of machine learning (ML) (1) in nursing by exploring its implications on patient care, nursing practices, and healthcare delivery. …”
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IMPROVING AGRICULTURAL YIELDS IN THE DEMOCRATIC REPUBLIC OF CONGO USING MACHINE LEARNING ALGORITHMS by Rodolphe Nsimba Malumba, Mardochee Longo Kayembe, Fiston Chrisnovic Balanganayi Kabutakapua, Bopatriciat Boluma Mangata, Trésor MAZAMBI KILONGO, Rufin Tabiaki Tandele, Emmanuel Ntanyungu Ndizieye, Parfum Bukanga Christian

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Dataset Construction Using Item Response Theory for Educational Machine Learning Competitions by Takeaki Sakabe, Yuko Sakurai, Emiko Tsutsumi, Satoshi Oyama

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Advancing food security: The role of machine learning in pathogen detection by Helen Onyeaka, Adenike Akinsemolu, Taghi Miri, Nnabueze Darlington Nnaji, Clinton Emeka, Phemelo Tamasiga, Gu Pang, Zainab Al-sharify

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Same data, different results? Machine learning approaches in bioacoustics by Kaja Wierucka, Derek Murphy, Stuart K. Watson, Nikola Falk, Claudia Fichtel, Julian León, Stephan T. Leu, Peter M. Kappeler, Elodie F. Briefer, Marta B. Manser, Nikhil Phaniraj, Marina Scheumann, Judith M. Burkart

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Pretreatment Methods for Enhancing Machine Learning Performance on Metabolomics Data by Rustam

“…Pretreatment methods are critical for metabolomics data analysis, yet their impact on machine learning performance remains insufficiently explored. …”
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A data-to-forecast machine learning system for global weather by Xiuyu Sun, Xiaohui Zhong, Xiaoze Xu, Yuanqing Huang, Hao Li, J. David Neelin, Deliang Chen, Jie Feng, Wei Han, Libo Wu, Yuan Qi

“…Here, we introduce FuXi Weather, a machine learning-based global forecasting system that assimilates multi-satellite data and is capable of cycling DA and forecasting. …”
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Small earthquake location via machine learning with insufficient data by Ji Zhang, Aitaro Kato, Huiyu Zhu, Jie Zhang

“…Traditional seismic location methods based on travel time and waveform analysis may be ineffective for such events, while traditional single-station location methods require high signal-to-noise ratio (SNR) data. …”
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Machine Learning with Administrative Data for Energy Poverty Identification in the UK by Lin Zheng, Eoghan McKenna

“…We develop machine learning models using data from the English Housing Survey that serves as a proxy for administrative data. …”
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