Stochasticity as a solution for overfitting—A new model and comparative study on non-invasive EEG prospects by Yousef A. Radwan, Eslam Ahmed Mohamed, Donia Metwalli, Mariam Barakat, Anas Ahmed, Antony E. Kiroles, Sahar Selim

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Forecasting the Probability of Large Rates of Change of the Geomagnetic Field in the UK: Timescales, Horizons, and Thresholds by A. W. Smith, C. Forsyth, I. J. Rae, T. M. Garton, T. Bloch, C. M. Jackman, M. Bakrania

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Development and validation of a risk prediction model for acute kidney injury in coronary artery disease by Ming Ye, Chang Liu, Duo Yang, Hai Gao

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Geospatial Data and Deep Learning Expose ESG Risks to Critical Raw Materials Supply: The Case of Lithium by Christopher J. M. Lawley, Marcus Haynes, Bijal Chudasama, Kathryn Goodenough, Toni Eerola, Artem Golev, Steven E. Zhang, Junhyeok Park, Eleonore Lèbre

Subjects: “…machine learning…”
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Artificial Intelligence-Powered Materials Science by Xiaopeng Bai, Xingcai Zhang

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Machine learning models for predicting the bearing capacity of shallow foundations: A Comparative study and sensitivity analysis by Hamid Mohammadnezhad, Seyedmohammad Eslami

Subjects: “…machine learning…”
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Artificial intelligence driven innovations in biochemistry: A review of emerging research frontiers by Mohammed Abdul Lateef Junaid

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Rapid detection of drug abuse via tear analysis using surface enhanced Raman spectroscopy and machine learning by Yingbin Wang, Yulong Huang, Xiaobao Liu, Chishan Kang, Wenjie Wu

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A machine learning-based clinical predictive tool to identify patients at high risk of medication errors by Ammar Abdo, Lyse Gallay, Thibault Vallecillo, Justine Clarenne, Pauline Quillet, Vincent Vuiblet, Rudy Merieux

Subjects: “…Machine learning…”
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Machine learning-based estimation of crude oil-nitrogen interfacial tension by Safia Obaidur Rab, Subhash Chandra, Abhinav Kumar, Pinank Patel, Mohammed Al-Farouni, Soumya V. Menon, Bandar R. Alsehli, Mamata Chahar, Manmeet Singh, Mahmood Kiani

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Machine learning for classifying chronic kidney disease and predicting creatinine levels using at-home measurements by Brady Metherall, Anna K. Berryman, Georgia S. Brennan

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Prediction of GNSS Velocity Accuracies Using Machine Learning Algorithms for Active Fault Slip Rate Determination and Earthquake Hazard Assessment by Halil İbrahim Solak

Subjects: “…machine learning…”
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Comprehensive Analysis of Programmed Cell Death-Related Genes in Diagnosis and Synovitis During Osteoarthritis Development: Based on Bulk and Single-Cell RNA Sequencing Data by Zhou J, Jiao S, Huang J, Dai T, Xu Y, Xia D, Feng Z, Chen J, Li Z, Hu L, Meng Q

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Diabetes and Cataracts Development—Characteristics, Subtypes and Predictive Modeling Using Machine Learning in Romanian Patients: A Cross-Sectional Study by Adriana Ivanescu, Simona Popescu, Adina Braha, Bogdan Timar, Teodora Sorescu, Sandra Lazar, Romulus Timar, Laura Gaita

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Agricultural GDP exposure to drought and its machine learning-based prediction in the Jialing River Basin, China by Xinzhi Wang, Qingxia Lin, Zhiyong Wu, Yuliang Zhang, Changwen Li, Ji Liu, Shinan Zhang, Songyu Li

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Determining university’s readiness to implement AI technologies for personalizing educational paths by V. S. Starostin, K. A. Arzhanova, D. V. Dolgopolov, A. D. Ditrikh

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Effect of Feature Selection on the Prediction of Direct Normal Irradiance by Mohamed Khalifa Boutahir, Yousef Farhaoui, Mourade Azrour, Imad Zeroual, Ahmad El Allaoui

Subjects: “…machine learning…”
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Machine learning insights into early mortality risks for small cell lung cancer patients post-chemotherapy by Min Liang, Min Liang, Fuyuan Luo

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Modeling the determinants of attrition in a two-stage epilepsy prevalence survey in Nairobi using machine learning by Daniel M. Mwanga, Isaac C. Kipchirchir, George O. Muhua, Charles R. Newton, Damazo T. Kadengye, Abankwah Junior, Albert Akpalu, Arjune Sen, Bruno Mmbando, Charles R. Newton, Cynthia Sottie, Dan Bhwana, Daniel Mtai Mwanga, Damazo T. Kadengye, Daniel Nana Yaw, David McDaid, Dorcas Muli, Emmanuel Darkwa, Frederick Murunga Wekesah, Gershim Asiki, Gergana Manolova, Guillaume Pages, Helen Cross, Henrika Kimambo, Isolide S. Massawe, Josemir W. Sander, Mary Bitta, Mercy Atieno, Neerja Chowdhary, Patrick Adjei, Peter O. Otieno, Ryan Wagner, Richard Walker, Sabina Asiamah, Samuel Iddi, Simone Grassi, Sloan Mahone, Sonia Vallentin, Stella Waruingi, Symon Kariuki, Tarun Dua, Thomas Kwasa, Timothy Denison, Tony Godi, Vivian Mushi, William Matuja

Subjects: “…Machine learning…”
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Relationship analysis between deterioration of switch support and railway passenger comfort using machine learning by Sresakoolchai Jessada, Cheputeh Ni-Asri

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