Enhancing Feedback Quality at Scale: Leveraging Machine Learning for Learner-Centered Feedback by Ahmad Ari Aldino, Yi-Shan Tsai, Rafael Ferreira Mello, Dragan Gašević, Guanliang Chen

“…Employing a range of machine learning and deep learning techniques, including Random Forest, XGBoost, BERT, and GPT-3.5, we systematically investigated the effectiveness of different approaches for constructing classifiers to accurately categorize feedback into various learner-centered components. …”
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Learning <i>Effective Good</i> Variables from Physical Data by Giulio Barletta, Giovanni Trezza, Eliodoro Chiavazzo

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Correlation between Smart Mask and Knitted Coil Sensors Breathing Data by Matthew Setiawan, Muhammad Adil Malik, Kristel Fobelets

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Enhancing Typhoid Fever Diagnosis Based on Clinical Data Using a Lightweight Machine Learning Metamodel by Fariha Ahmed Nishat, M. F. Mridha, Istiak Mahmud, Meshal Alfarhood, Mejdl Safran, Dunren Che

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Revolutionizing Nursing and Midwifery Informatics Curriculum Evaluation in Ghana: A Data-Driven Machine Learning Approach by Iven Aabaah, Japheth Kodua Wiredu, Bakaweri Emmanuel Batowise, Nelson Abuba Seidu

“…This research assessed NMI educational programs in Ghana using machine learning techniques to analyze key factors influencing student performance, engagement, and satisfaction. …”
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Industrial multi-machine data aggregation, AI-ready data preparation, and machine learning for virtual metrology in semiconductor wafer and slider production by Feiyang Ou, Julius Suherman, Chao Zhang, Henrik Wang, Sthitie Bom, James F. Davis, Panagiotis D. Christofides

“…Smart Manufacturing is rooted in AI, Machine Learned (ML), and Data Synchronized (DS) modeling to tap into invaluable operating data. …”
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Predicting the impact of public events and mobility in Smart Cities by Elena Bellodi, Riccardo Zese, Carlo Petrovich, Angelo Frascella, Francesco Bertasi

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An annotated morphological dataset for Uzbek word forms: Towards rule-based and machine learning approachesMendeley Data by Nilufar Abdurakhmonova, Raima Shirinova, Rano Sayfullayeva, Davlatyor Mengliev, Bahodir Ibragimov, Manzura Ernazarova

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Accuracy Comparison of Machine Learning Algorithms on World Happiness Index Data by Sadullah Çelik, Bilge Doğanlı, Mahmut Ünsal Şaşmaz, Ulas Akkucuk

“…In conclusion, this study offers valuable information for more effective classification and analysis of World Happiness Index data by comparing the performance of various machine learning algorithms.…”
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Data-driven insights into groundwater quality: machine and deep learning approaches by Gift Mbuzi, Abdur Rashid Sangi, Baha Ihnaini, Anil Carie, Sruthi Sivarajan, Satish Anamalamudi

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Efficient Observation Time Window Segmentation for Administrative Data Machine Learning by Musa Taib, Geoffrey G. Messier

“…Machine learning models benefit when allowed to learn from temporal trends in time-stamped administrative data. …”
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Big Data, Machine Learning, Artificial Intelligence and Blockchain in Corporate Governance by Meiryani Meiryani, Dezie Leonarda Warganegara, Vidhiya Andini

“… The paper analyses the dynamics of scientific research in, and practical application of key Industry 4.0 technologies in corporate governance, namely big data, artificial intelligence, machine learning, and blockchain. …”
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Data-Driven Pavement Performance: Machine Learning-Based Predictive Models by Mohammad Fahad, Nurullah Bektas

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Predicting cancer risk using machine learning on lifestyle and genetic data by Mohamed Abdelmoaty Ahmed, Ahmed AbdelMoety, Asmaa Mohamed Ahmed Soliman

“…This study investigates the application of Machine Learning (ML) techniques to predict cancer risk based on a combination of genetic and lifestyle factors. …”
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Gravity Predictions in Data-Missing Areas Using Machine Learning Methods by Yubin Liu, Yi Zhang, Qipei Pang, Sulan Liu, Shaobo Li, Xuguo Shi, Shaofeng Bian, Yunlong Wu

“…In recent years, the rapid development of artificial intelligence has opened up a new opportunity for data prediction. In this study, utilizing the EGM2008 satellite gravity model, we conducted a comprehensive analysis of three machine learning algorithms—random forest, support vector machine, and recurrent neural network—and compared their performances against the traditional Kriging interpolation method. …”
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Prediction of dialysis adequacy using data-driven machine learning algorithms by Yi-Chen Liu, Ji-Ping Qing, Rong Li, Juan Chang, Li-Xia Xu

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Detection of Banana Diseases Based on Landsat-8 Data and Machine Learning by Renata Retkute, Kathleen S. Crew, John E. Thomas, Christopher A. Gilligan

“…Recent outbreaks of banana diseases are threatening the global banana industry and smallholder livelihoods. Remote sensing data offer the potential to detect the presence of disease, but formal analysis is needed to compare inferred disease data with observed disease data. …”
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Intelligent corrosion analysis and life prediction of ductile iron pipe systems using machine learning and electrochemical sensors by Bingqin Wang, Long Zhao, Yongfeng Chen, Lingsheng Zhu, Chao Liu, Xuequn Cheng, Xiaogang Li

“…A corrosion decision model based on a machine learning framework was developed for data mining. …”
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Computational modelling of immunological mechanisms: From statistical approaches to interpretable machine learning by María Rodríguez Martínez, Matteo Barberis, Anna Niarakis

Subjects: “…Interpretable machine learning…”
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Retraining and evaluation of machine learning and deep learning models for seizure classification from EEG data by Juan Pablo Carvajal-Dossman¹, Laura Guio, Danilo García-Orjuela, Jennifer J. Guzmán-Porras, Kelly Garces, Andres Naranjo, Silvia Juliana Maradei-Anaya, Jorge Duitama

“…We expect that the retrained models and the data available in this work will contribute to the integration of machine learning techniques as tools to improve the accuracy of diagnosis in clinical settings.…”
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