Support Vector and Linear Regression Machine Learning Model on Amperometric Signals to Predict Glucose Concentration and Hematocrit Volume by Kirti Sharma, Pawan K. Tiwari, Sanjay Kumar Sinha

“…The dataset employed for this research is sourced from clinically validated electrochemical glucose sensors (commonly referred to as glucose strips). …”
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Analysis of Multivariate Indoor Building Data: A Comparative Study of Time-Series Clustering Methods by Quoc-Dung Ngo, Ly-Huynh Phan

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Combination of Music, Artificial Intelligence, and Brainwaves for the Promotion of Mental Well-Being by Georgios Karachalios, Evina Makaroni

“…The convergence of music, neuroscience, and artificial intelligence presents a highly innovative field of research and application, with significant potential for addressing various issues related to mental health and human well-being. …”
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Diagnosis and Management of Alzheimer’s Disease in Primary Care: A Real-World Study in Ontario, Canada by Zahinoor Ismail, Melanie Wilson, Hany Khalifa, Daniela Belovich, Eileen Shaw, Tram Pham, Suzanne McMullen, Yuhao Chen, Nafiz Sadman, Jackson Cai, Farhana Zulkernine, David Barber

“…Objective: To understand the real-world clinical practice patterns and variation in Alzheimer’s disease (AD) diagnostic and screening tool utilization by primary care physicians (PCPs), including tools used for assessing dementia/AD severity and subsequent treatment patterns. …”
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Optimizing Energy Forecasting Using ANN and RF Models for HVAC and Heating Predictions by Khaled M. Salem, Javier M. Rey-Hernández, A. O. Elgharib, Francisco J. Rey-Martínez

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Cheating Detection in Online Exams Using Deep Learning and Machine Learning by Bahaddin Erdem, Murat Karabatak

“…For regression and classification, deep neural network (DNN) from deep learning algorithms and support vector machine (SVM), decision trees (DTs), k-nearest neighbor (KNN), random forest (RF), logistic regression (LR), and extreme gradient boosting (XGBoost) algorithms from machine learning algorithms were used. …”
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Explainable AI-based suicidal and non-suicidal ideations detection from social media text with enhanced ensemble technique by Daniyal Alghazzawi, Hayat Ullah, Naila Tabassum, Sahar K. Badri, Muhammad Zubair Asghar

“…Our methodology, along with an updated ensemble method, bridges the gap between Explainable AI and leverages a variety of machine learning algorithms to improve predictive accuracy. By leveraging Explainable AI’s interpretability to analyze the features, the model elucidates the reasoning behind its classifications leading to a comprehension of hidden patterns associated with suicidal ideations. …”
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An Innovative Analysis of Time Series-Based Detection Models for Improved Cancer Detection in Modern Healthcare Environments by Uma Shankari Srinivasan, Venkat Pavithra, Kaliappan Sutha, Sridevi Ramachandiran, Nallathambi Indumathi

“…This enhanced version of time series analysis incorporates multiple layers of data sources and uses advanced machine learning algorithms to identify patterns that could signal the presence of a tumor. …”
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Integrating asthma care guidelines into primary care electronic medical records: a review focused on Canadian knowledge translation tools by Matheson McFarlane, Alison Morra, M. Diane Lougheed

“…Additionally, the priorities of primary care physicians should be considered in future KT tool research to improve end-user uptake and overall asthma management practices.…”
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Modeling Flood Susceptibility Utilizing Advanced Ensemble Machine Learning Techniques in the Marand Plain by Ali Asghar Rostami, Mohammad Taghi Sattari, Halit Apaydin, Adam Milewski

“…In this case study, flood susceptibility patterns in the Marand Plain, located in the East Azerbaijan Province in northwest Iran, were analyzed using five machine learning (ML) algorithms: M5P model tree, Random SubSpace (RSS), Random Forest (RF), Bagging, and Locally Weighted Linear (LWL). …”
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The effective landscape design parameters with high reflective hardscapes: guidelines for optimizing human thermal comfort in outdoor spaces by design -a case on hot arid climate w... by Reham A. Abdelwahab, Ahmed A. Fekry, Reham El-Dessuky Hamed

“…Through generative design algorithms, an optimized framework was developed to identify effective strategies for urban cooling. …”
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The role of epigenetic regulation in pancreatic ductal adenocarcinoma progression and drug response: an integrative genomic and pharmacological prognostic prediction model by Kang Fu, Junzhe Su, Yiming Zhou, Xiaotong Chen, Xiao Hu

“…A machine learning-based prognostic model was constructed using multiple algorithms, including Lasso and Random Survival Forest. …”
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Intelligent traffic congestion forecasting using BiLSTM and adaptive secretary bird optimizer for sustainable urban transportation by Lalitha Krishnasamy, Siva C, Rajesh Kumar Dhanaraj, Mahmoud Ahmad Al-Khasawneh, Taher Al-Shehari, Nasser A. Alsadhan, Shitharth Selvarajan

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Towards a computer-assisted assessment of imitation in children with autism spectrum disorder based on a fine-grained analysis by Rujing Zhang, Jingying Chen, Xiaodi Liu, Yanling Gan, Guangshuai Wang

“…In this process, several quantitative indicators were applied to quantify the children’s imitation ability based on a fine-grained analysis of their visual attention and motor execution patterns. Then, three classic machine-learning algorithms were employed to explore whether the indicators could efficiently classify children with imitation difficulties. …”
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An Elderly Fall Detection Method Based on Federated Learning and Extreme Learning Machine (Fed-ELM) by Zhigang Yu, Jiahui Liu, Mingchuan Yang, Yanmin Cheng, Jie Hu, Xinchi Li

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Computational intelligence investigations on evaluation of salicylic acid solubility in various solvents at different temperatures by Adel Alhowyan, Wael A. Mahdi, Ahmad J. Obaidullah

“…Abstract This research shows the utilization of various tree-based machine learning algorithms with a specific focus on predicting Salicylic acid solubility values in 13 solvents. …”
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What factors enhance students' achievement? A machine learning and interpretable methods approach. by Hui Mao, Ribesh Khanal, ChengZhang Qu, HuaFeng Kong, TingYao Jiang

“…Prior research on student achievement has typically examined isolated factors or bivariate correlations, failing to capture the complex interplay between learning behaviors, pedagogical environments, and instructional design. …”
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AI-Driven Framework for Evaluating Climate Misinformation and Data Quality on Social Media by Zeinab Shahbazi, Rezvan Jalali, Zahra Shahbazi

“…Data quality is defined using key dimensions of credibility, accuracy, relevance, and sentiment polarity, and a pipeline is developed using transformer-based NLP models, sentiment classifiers, and misinformation detection algorithms. The system processes user-generated content to detect sentiment drift, engagement patterns, and trustworthiness scores. …”
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Enhancing privacy in clustering and data mining: A novel approach for sensitive data protection by Haythem Hayouni

“…We provide formal definitions and algorithms for each module and demonstrate their integration in a unified architecture. …”
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Review of Methods and Models for Forecasting Electricity Consumption by Kamil Misiurek, Tadeusz Olkuski, Janusz Zyśk

“…The authors conducted a comparative analysis of various models, such as autoregressive models, neural networks, fuzzy logic systems, hybrid models, and evolutionary algorithms. Particular attention was paid to the effectiveness of these methods in the context of variable input data, such as weather conditions, seasonal fluctuations, and changes in energy consumption patterns. …”
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