Social Media Suicide Watch by Katherine Prothro

“…This model includes direct user alerts, safety planning, and opt-in data-sharing with mental health professionals. …”
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Simulating urban growth through case-based reasoning by X. Ye, W. W. Yu, W. H. Yu, L. N. Lv

“…However, CBR analyses of land-use changes are difficult to apply in the study of urban growth due to shortcomings in the case structure and model algorithms. In response, this study proposes a three-step urban-growth simulation model based on CBR (UGSCBR). …”
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EcoTaskSched: a hybrid machine learning approach for energy-efficient task scheduling in IoT-based fog-cloud environments by Asfandyar Khan, Faizan Ullah, Dilawar Shah, Muhammad Haris Khan, Shujaat Ali, Muhammad Tahir

“…To evaluate performance, the proposed EcoTaskSched model demonstrated superiority by significantly reducing energy consumption and improving job completion rates compared to baseline models. …”
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CTAB modified SnO₂ PEDOT PSS heterojunction humidity sensor with enhanced sensitivity stability and machine learning evaluation by Poundoss Chellamuthu, Kirubaveni Savarimuthu, M Gulam Nabi Alsath, R. Krishnamoorthy, Yuvaraj T, Feras Alnaimat, Mohammad Shabaz

“…Furthermore, to validate real-time application feasibility, machine learning (ML) algorithms were implemented to model and predict sensor behavior. …”
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Human multiethnic radiogenomics reveals low-abundancy microRNA signature in plasma-derived extracellular vesicles for early diagnosis and molecular subtyping of pancreatic cancer by Jianying Xu, Wenjie Shi, Yi Zhu, Chao Zhang, Julia Nagelschmitz, Maximilian Doelling, Sara Al-Madhi, Ujjwal Mukund Mahajan, Maciej Pech, Georg Rose, Roland Siegfried Croner, Guoliang Zheng, Christoph Kahlert, Ulf Dietrich Kahlert

“…Radiomics features were extracted and analyzed using the limma package, with feature selection conducted via the Boruta algorithm and model construction through Least Absolute Shrinkage and Selection Operator regression. …”
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Transfer Learning for Induction Motor Health Monitoring: A Brief Review by Prashant Kumar

“…Transfer learning utilizes pretrained models to address new tasks with limited labeled data. …”
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The outcome prediction method of football matches by the quantum neural network based on deep learning by Yang Sun, Hongyang Chu

“…The optimized QNN model has an improvement of more than 20.5% in precision, an enhancement of over 23.2% in recall, and an increase of over 22.3% and 21.8% in accuracy and F1 score. …”
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No-load and on-load performance analysis of 10-stator-slots five phase flux switching machines with non-overlapped winding configurations by Muhammad Yousuf, Faisal Khan, Ahmed Tameemi, Wasiq Ullah

“…An evolutionary optimization process based on the genetic algorithm (GA) integrated with the JMAG software is executed to optimize the machine models, resulting in significant improvements in the analyzed WFFS machine models. …”
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Detección y diagnóstico de fallas en motores mediante el análisis de vibraciones aplicando técnicas de inteligencia artificial. by Jair Elías Araujo Vargas, Dilan Yesid Franklin Coronel, Victor Manuel Arias Ruiz

“…Thus, artificial intelligence algorithms demonstrated high accuracy in fault detection and resolution, identifying various types of problems in a timely manner; the models contributed significantly to the overall analysis, offering a more reliable approach to predictive industrial maintenance, paving the way for future improvements and the adoption of new, more robust and adaptable algorithms.…”
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Predicting child mortality determinants in Uttar Pradesh using Machine Learning: Insights from the National Family and Health Survey (2019–21) by Pinky Pandey, Sacheendra Shukla, Niraj Kumar Singh, Mukesh Kumar

“…Four machine learning algorithms—Random Forests, Logistic Regression, K-Nearest Neighbors (KNN), and Naive Bayes—were applied alongside a traditional logistic regression model. …”
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Interpretable artificial intelligence (AI) for cervical cancer risk analysis leveraging stacking ensemble and expert knowledge by Priyanka Roy, Mahmudul Hasan, Md Rashedul Islam, Md Palash Uddin

“…A hybrid feature selection method is proposed to enhance predictive accuracy and stability, alongside evaluation of multiple classification algorithms. The integration of explainable artificial intelligence (XAI) techniques ensures transparency and interpretability in model decisions. …”
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Explainable AI-driven intelligent system for precision forecasting in cardiovascular disease by Anas Bilal, Abdulkareem Alzahrani, Khalid Almohammadi, Muhammad Saleem, Muhammad Sajid Farooq, Raheem Sarwar

“…Typically, predicting CVDs involves using statistical models and other forms of standard machine learning. …”
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Targeted inhibition of Gus-expressing Enterococcus faecalis to promote intestinal stem cell and epithelial renovation contributes to the relief of irinotecan chemotoxicity by dehyd... by Ruiyang Gao, Bei Yue, Cheng Lv, Xiaolong Geng, Zhilun Yu, Hao Wang, Beibei Zhang, Fangbin Ai, Ziyi Wang, Donghui Liu, Zhengtao Wang, Kaixian Chen, Wei Dou

“…The Partial Least Squares Path Model (PLS-PM) algorithm initially links E. faecalis to dysregulated epithelial renovation. …”
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Hybrid CNN-LSTM With Attention Mechanism for Robust Credit Card Fraud Detection by Iman Akour, Nour Mohamed, Said Salloum

“…Our hybrid CNN-LSTM-Attention model improves fraud detection by addressing both spatial and temporal data features while dynamically focusing on critical elements. …”
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Leveraging machine learning for enhanced and interpretable risk prediction of venous thromboembolism in acute ischemic stroke care. by Youli Jiang, Ao Li, Zhihuan Li, Yanfeng Li, Rong Li, Qingshi Zhao, Guisu Li

“…Predictive models were developed using machine learning algorithms, including Gradient Boosting Machine (GBM), Random Forest (RF), and Logistic Regression (LR). …”
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Interpretable prediction of hospital mortality in bleeding critically ill patients based on machine learning and SHAP by Bingkui Ren, Yuping Zhang, Siying Chen, Jinglong Dai, Junci Chong, Yifei Zhong, Mengkai Deng, Shaobo Jiang, Zhigang Chang

“…Enhanced model transparency through SHAP explanations may facilitate clinical adoption by improving trust in model reliability.…”
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Democratization of Crop Irrigation: A Socio-Technical Optimization Approach Using Particle Swarm Optimization by Hasna Elalaoui Elabdallaoui, Youssef Mourdi, Abdelaziz ElFazziki, Mohamed Sadgal

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Comparison of tone mapping methods during images processing on liquid crystal displays by A. V. Sycev, A. A. Stepanov, A. G. Smirnov, K. .. Blankenbach

“…Image enhancement algorithms improve readability on liquid crystal displays under bright ambient light conditions and are the theme of many researchers and developers. …”
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Balancing Predictive Performance and Interpretability in Machine Learning: A Scoring System and an Empirical Study in Traffic Prediction by Fabian Obster, Monica I. Ciolacu, Andreas Humpe

“…As Machine Learning algorithms become increasingly embedded in decision-making processes, particularly for traffic management and other high-level commitment applications, concerns regarding the transparency and trustworthiness of complex ‘black-box’ models have grown. …”
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Polymer electrolyte membrane fuel cell performance Revolutionized: Artificial intelligence-validated asymmetric flow channels enhance mass transport via hybrid analytical-numerical... by Nima Ahmadi, Ghader Rezazadeh

“…Experimental validation confirms a current density improvement of up to 5.6 % over conventional designs, while Artificial Intelligence (AI)-driven optimization via a hybrid Convolutional Neural Network and Genetic Algorithm independently identifies the same optimal configuration. …”
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