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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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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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

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Machine Learning for Prediction of Relapses in Multiple Drug Resistant Tuberculosis Patients by A. S. Аlliluev, O. V. Filinyuk, E. E. Shnаyder, S. V. Аksenov

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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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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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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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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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Comparative study on Functional Machine learning and Statistical Methods in Disease detection and Weed Removal for Enhanced Agricultural Yield by Sudha D., Menaga D.

“…The technology has developed to rectify the problems using some machine learning algorithms like Random Forest algorithms, Decision trees, Naïve Bayes, KNN, K-Means clustering, Support vector machines. …”
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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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