Machine Learning Accurately Predicts Need for Critical Care Support in Patients Admitted to Hospital for Community-Acquired Pneumonia by George S. Chen, BSc, Terry Lee, PhD, Jennifer L.Y. Tsang, MD, Alexandra Binnie, MD, Anne McCarthy, MD, Juthaporn Cowan, MD, Patrick Archambault, MD, Francois Lellouche, MD, Alexis F. Turgeon, MD, MSc, Jennifer Yoon, MD, Francois Lamontagne, MD, Allison McGeer, MD, Josh Douglas, MD, Peter Daley, MD, Robert Fowler, MD, David M. Maslove, MD, Brent W. Winston, MD, Todd C. Lee, MD, Karen C. Tran, MD, Matthew P. Cheng, MD, Donald C. Vinh, MD, John H. Boyd, MD, Keith R. Walley, MD, Joel Singer, PhD, John C. Marshall, MD, James A. Russell, MD, for the Community-Acquired Pneumonia: Toward InnoVAtive Treatment (CAPTIVATE) Investigators

“…This retrospective observational study trained separate models using random-forest classifier (RFC), support vector machines (SVMs), Extreme Gradient Boosting (XGBoost), and multilayer perceptron (MLP) to predict three endpoints: eventual use of invasive ventilation, vasopressors, and RRT during hospitalization. …”
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Hair loss: The role of nutritional support in a comprehensive approach to hair loss treatment by Anna I. Krylova, Spartak F. Kaiumov, Maria I. Vasil’eva

“…The participants were randomly assigned to three distinct groups. The first group was treated with Pantovigar orally, in conjunction with a topical lotion designed to combat hair loss, which contained the active ingredient Microxidil. …”
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A Systematic Literature Review on the Application of Machine Learning for Predicting Stunting Prevalence in Indonesia (2020–2024) by Emilda Indrisari, Hidayat Febiansyah, Bambang Adiwinoto

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Exploring the VAK model to predict student learning styles based on learning activity by Ahmed Rashad Sayed, Mohamed Helmy Khafagy, Mostafa Ali, Marwa Hussien Mohamed

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Google Earth Engine-based Mangrove Mapping and Change Detections for Sustainable Development in Tien Yen District, Quang Ninh Province, Vietnam by M. H. Nguyen, N. T. Nguyen, G. Y. I. Ryadi, M. V. Nguyen, T. L. Duong, C.-H. Lin, T. B. Nguyen

“…Four supervised classification algorithms, including Random Forest (RF), Support Vector Machine (SVM), Naïve Bayes classifier, and Classification and Regression Trees (CART) have been implemented on GEE platform to select the best algorithm to produce spatial-temporal mangrove maps, then change detection of mangroves is performed. …”
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AI-Driven Predictive Maintenance for Workforce and Service Optimization in the Automotive Sector by Şenda Yıldırım, Ahmet Deniz Yücekaya, Mustafa Hekimoğlu, Meltem Ucal, Mehmet Nafiz Aydin, İrem Kalafat

“…Additionally, this predictive approach supports workforce planning and scheduling within after-sales service centers, aligning with AI-driven labor optimization frameworks such as those explored in the AI4LABOUR project. Four algorithms in machine learning—Decision Tree, Random Forest, LightGBM (LGBM), and Extreme Gradient Boosting (XGBoost)—were assessed for their forecasting capabilities. …”
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Hierarchical Classification of Variable Stars Using Deep Convolutional Neural Networks by Mahdi Abdollahi, Nooshin Torabi, Sadegh Raeisi, Sohrab Rahvar

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EVOLUTION OF TREATMENT OF CANCER OF THE MAJOR DUODENAL PAPILLA by D. V. Nazarova, R. I. Rasulov, K. G. Zubrinsky, G. I. Sogolov

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Deepfake Audio Detection for Urdu Language Using Deep Neural Networks by Omair Ahmad, Muhammad Sohail Khan, Salman Jan, Inayat Khan

“…However, most of these solutions are trained on datasets in English, Portuguese, French, and Spanish, expressing concerns about their correctness for other languages. The main goal of the research presented in this paper is to evaluate the effectiveness of deep learning neural networks in detecting Deepfake audios in the Urdu language. …”
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A combination of urinary biomarker panel and PancRISK score for earlier detection of pancreatic cancer: A case-control study. by Silvana Debernardi, Harrison O'Brien, Asma S Algahmdi, Nuria Malats, Grant D Stewart, Marija Plješa-Ercegovac, Eithne Costello, William Greenhalf, Amina Saad, Rhiannon Roberts, Alexander Ney, Stephen P Pereira, Hemant M Kocher, Stephen Duffy, Oleg Blyuss, Tatjana Crnogorac-Jurcevic

“…Training and validation datasets for controls and PDAC samples were obtained after random division of the whole available dataset in a 1:1 ratio. …”
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Habitat suitability modeling to improve conservation strategy of two highly-grazed endemic plant species in saint Catherine Protectorate, Egypt by Mohamed M. El-Khalafy, Eman T. El-Kenany, Alshymaa Z. Al-Mokadem, Salma K. Shaltout, Ahmed R. Mahmoud

“…In our analysis, we included the incorporation of bioclimatic variables into the SDM modeling process using four main algorithms: generalized linear model (GLM), Random Forest (RF), Boosted Regression Trees (BRT), and Support Vector Machines (SVM) in an ensemble model. …”
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Certainty of Linear Interrelation of Technical and Economic Parameters of Power Units of 300 МWt Thermal Power Stations by E. M. Farhadzadeh, A. Z. Muradaliyev, T. K. Rafiyeva, A. A. Rustamova

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Analysis and Identification of Factors Influencing the Survival of Burn Injury Patients with an Artificial Intelligence Approach by Sara Hashemi, Shahla Faramarzi, Laya Rahmani Pirouz, Azita Yazdani

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Groundwater pollution risk assessment in typical coal-related industry agglomeration area by Lai ZHOU, Yanzhuo LIU, Zenggang QI, Lei WANG, Lei MENG, Qiyan FENG, Yanqing RONG

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Machine-Learning-Driven Analysis of Wear Loss and Frictional Behavior in Magnesium Hybrid Composites by Barun Haldar, Hillol Joardar, Arpan Kumar Mondal, Nashmi H. Alrasheedi, Rashid Khan, Murugesan P. Papathi

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Optimal Identification for Dynamic PV Cell Parameter Based on a Data-Extension-Driven Method by Yun Long, Youfei Lu, Li Wang, Tao Bao, Chen Chen

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Study on debris flow vulnerability of ensemble learning model based on spy technology A case study of upper Minjiang river basin by Yutao Chen, Ning Li, Fucheng Xing, Han Xiang, Zilong Chen

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Short Term Photovoltaic Power Combination Prediction Method Based on Similar Day Selection and Data Reconstruction by Qingbin CHEN, Genghuang YANG, Liqing GENG, Juan SU, Jingsheng SUN

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A systematic review of Machine Learning and Deep Learning approaches in Mexico: challenges and opportunities by José Luis Uc Castillo, Ana Elizabeth Marín Celestino, Diego Armando Martínez Cruz, José Tuxpan Vargas, José Alfredo Ramos Leal, Janete Morán Ramírez

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Identification of gene signatures and potential pharmaceutical candidates linked to COVID-19-related depression based on gene expression profiles by Shaojun Chen, Yiyuan Luo, Lihua Zhang

“…Subsequently, we employed two machine learning analyses—least absolute shrinkage and selection operator (LASSO) and random forest algorithms– to pinpoint shared hub gene between the two diseases. …”
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