Predicting stroke with machine learning techniques in a sub-Saharan African population by Benjamin Segun Aribisala, Deirdre Edward, Godwin Ogbole, Onoja M. Akpa, Segun Ayilara, Fred Sarfo, Olusola Olabanjo, Adekunle Fakunle, Babafemi Oluropo Macaulay, Joseph Yaria, Joshua Akinyemi, Albert Akpalu, Kolawole Wahab, Reginald Obiako, Morenikeji Komolafe, Lukman Owolabi, Godwin Osaigbovo, Akinkunmi Paul Okekunle, Arti Singh, Philip Ibinaye, Osahon Osawata, Adeniyi Sunday, Ijezie Chukwuonye, Carolyn Jenkins, Hemant K. Tiwari, Okechukwu Ogah, Ruth Y. Laryea, Daniel T. Lackland, Oyedunni Arulogun, Omotolani Ajala, Rufus Akinyemi, Bruce Ovbiagele, Steffen Sammet, Mayowa Owolabi

“…Conclusion: Machine Learning algorithms predicted stroke occurrence employing major risk factors in Sub-Saharan Africa better than regression models. …”
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Clinical Guidelines of the Russian Society for the Study of the Liver, Russian Gastroenterological Association, Russian Society for the Prevention of Non-Communicable Diseases, Rus... by V. T. Ivashkin, O. M. Drapkina, M. V. Maevskaya, K. L. Raikhelson, S. V. Okovityi, M. S. Zharkova, V. R. Grechishnikova, D. I. Abdulganieva, S. A. Alekseenko, M. D. Ardatskaya, I. G. Bakulin, N. V. Bakulina, P. O. Bogomolov, V. V. Breder, E. V. Vinnitskaya, N. I. Geyvandova, E. V. Golovanova, V. B. Grinevich, V. L. Doshchitsin, E. N. Dudinskaya, E. V. Ershova, K. B. Kodzoeva, I. V. Kozlova, K. A. Komshilova, Yu. V. Konev, N. V. Korochanskaya, Yu. V. Kotovskaya, Yu. A. Kravchuk, I. D. Loranskaya, I. V. Maev, A. I. Martynov, S. N. Mekhtiev, E. E. Mishina, M. Yu. Nadinskaia, I. G. Nikitin, M. F. Osipenko, O. D. Ostroumova, Ch. S. Pavlov, N. V. Pogosova, V. G. Radchenko, G. E. Roytberg, R. G. Saifutdinov, A. A. Samsonov, P. V. Seliverstov, S. I. Sitkin, L. V. Tarasova, A. I. Tarzimanova, O. N. Tkacheva, E. I. Tkachenko, E. A. Troshina, S. V. Turkina, Yu. P. Uspenskiy, Yu. A. Fominykh, O. V. Khlynova, Yu. V. Tsyganova, M. Sh. Shamkhalova, O. O. Sharkhun, M. V. Shestakova

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Responsible AI in structural engineering: a framework for ethical use by Vagelis Plevris, Haidar Hosamo

“…This study addresses these issues through eight fictional but realistic case studies that illustrate plausible ethical dilemmas, such as algorithmic bias in predictive models and tensions between AI-generated recommendations and human engineering judgment. …”
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Enhanced aquila optimizer for global optimization and data clustering by Laith Abualigah, Saleh Ali Alomari, Mohammad H. Almomani, Raed Abu Zitar, Hazem Migdady, Kashif Saleem, Aseel Smerat, Vaclav Snasel, Amir H. Gandomi

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AI IS LEARNING HOW TO WRITE. ETHICAL PROBLEMS FOR JOURNALISM by Dan Valeriu VOINEA

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Unobtrusive Sleep Posture Detection Using a Smart Bed Mattress with Optimally Distributed Triaxial Accelerometer Array and Parallel Convolutional Spatiotemporal Network by Zhuofu Liu, Gaohan Li, Chuanyi Wang, Vincenzo Cascioli, Peter W. McCarthy

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Deciphering the complex links between inflammatory bowel diseases and NAFLD through advanced statistical and machine learning analysis by Deepak Kumar, Brijesh Bakariya, Chaman Verma, Zoltán Illés

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A multistate transition model for survival estimation in randomized trials with treatment switching and a cured subgroup by Haixia Hu, Ling Wang, Kejian Wu, Wei Ge, Jielai Xia, Chen Li

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Student dropout prediction through machine learning optimization: insights from moodle log data by Markson Rebelo Marcolino, Thiago Reis Porto, Tiago Thompsen Primo, Rafael Targino, Vinicius Ramos, Emanuel Marques Queiroga, Roberto Munoz, Cristian Cechinel

“…These findings underscore the potential of targeted machine learning approaches to facilitate early identification of at-risk students, thereby enabling timely interventions and improving educational outcomes.…”
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Optimization of the prognosis of postoperative complications in patients with breast cancer by L. A. Trusova

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The Spatial and Dynamic Monitoring in Ensuring the Management of Energy Security of Enterprises by Budanov Mykola P.

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A Machine Learning Framework for Student Retention Policy Development: A Case Study by Sidika Hoca, Nazife Dimililer

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Development and evaluation of machine learning training strategies for neonatal mortality prediction using multicountry data by Gabriel Ferreira dos Santos Silva, Roberta Moreira Wichmann, Francisco Costa da Silva Junior, Alexandre Dias Porto Chiavegatto Filho

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Artificial Intelligence in Journalism: Bibliometric Analysis of Publication Activity by Violetta A. Zorina

“…Artificial intelligence is changing the algorithms for the development of various spheres of society, is actively being introduced into the media industry, producing new opportunities and social risks. …”
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Leveraging AI-Generated Virtual Speakers to Enhance Multilingual E-Learning Experiences by Sergio Miranda, Rosa Vegliante

“…The e-learning platform used is a customized Moodle, and three courses were developed: “Mental Wellbeing in Mining”, “Rescue in the Mine”, and “Risk Assessment” for a European ERASMUS+ project. …”
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Artificial intelligence in academic research: Benefits, challenges, and ethical dimensions in doctoral studies by Zaki EL HANI, Jaouad KARROUM, Abdelmajid ELOUADI, Aniss MOUMEN

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Embracing or rejecting AI? A mixed-method study on undergraduate students’ perceptions of artificial intelligence at a private university in China by Yifu Li, Nilo Jayoma Castulo, Xiaoyuan Xu, Xiaoyuan Xu

“…This study contributes to the discourse on AI integration in higher education by highlighting students’ nuanced perceptions and balancing their benefits with potential risks. …”
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Training Future Library Professionals to Use Neural Networks in Socio-Cultural Activities by E. Yu. Kozlenko

“…In training library and information workers on the use of neural networks in socio-cultural activities the key conditions are as follows: study and analysis of the experience of libraries in the use of neural networks in sociocultural activities; introduction into the educational programme of theoretical and practical blocks on the use of neural networks in the sociocultural activities of libraries; accounting and risk management of the use of neural networks. …”
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A longitudinal study of interplay between student engagement and self-regulation by Sami Heikkinen, Mohammed Saqr, Jonna Malmberg, Matti Tedre

“…This research provides actionable insights for developing targeted support strategies, including early warning systems for at-risk students and personalized scaffolding approaches based on students' behavioural patterns. …”
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Metabolic pathway activation and immune microenvironment features in non-small cell lung cancer: insights from single-cell transcriptomics by Yanru Liu, Yanru Liu, Yanru Liu, Hanmin Liu, Hanmin Liu, Ying Xiong, Ying Xiong

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