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Frontiers in Artificial Intelligence|November 21, 2024
Advancing smart city factories: enhancing industrial mechanical operations via deep learning techniquesWilliam Villegas-Ch, Jaime Govea, Walter Gaibor-Naranjo, et al.
Frontiers in Artificial Intelligence|November 20, 2024
Catalyzing IVF outcome prediction: exploring advanced machine learning paradigms for enhanced success rate prognosticationSeyed-Ali Sadegh-Zadeh, Sanaz Khanjani, Shima Javanmardi, et al.
Frontiers in Artificial Intelligence|March 14, 2025
Comparison of 3D and 2D area measurement of acute burn wounds with LiDAR technique and deep learning modelChe Wei Chang, Hanwei Wang, Feipei Lai, et al.
Frontiers in Artificial Intelligence|March 11, 2025
Transfer learning for predicting of gross domestic product growth based on remittance inflows using RNN-LSTM hybrid model: a case study of The GambiaHaruna Jallow, Ronald Waweru Mwangi, Alieu Gibba, et al.
Frontiers in Artificial Intelligence|October 24, 2024
Beyond the stereotypes: Artificial Intelligence image generation and diversity in anesthesiologyMia Gisselbaek, Laurens Minsart, Ekin Köselerli, et al.
Frontiers in Artificial Intelligence|October 22, 2024
Opportunities and challenges of using generative AI to personalize educational assessmentBurcu Arslan, Blair Lehman, Caitlin Tenison, et al.
Frontiers in Artificial Intelligence|October 18, 2024
Enhancing diagnostic accuracy in symptom-based health checkers: a comprehensive machine learning approach with clinical vignettes and benchmarkingLeila Aissaoui Ferhi, Manel Ben Amar, Fethi Choubani, et al.
Frontiers in Artificial Intelligence|October 17, 2024
Modeling disagreement in automatic data labeling for semi-supervised learning in Clinical Natural Language ProcessingHongshu Liu, Nabeel Seedat, Julia Ive
Frontiers in Artificial Intelligence|October 24, 2024
Predicting clinical trial success for Clostridium difficile infections based on preclinical dataFangzhou Li, Jason Youn, Christian Millsop, et al.
Frontiers in Artificial Intelligence|October 3, 2024
David vs. Goliath: comparing conventional machine learning and a large language model for assessing students' concept use in a physics problemFabian Kieser, Paul Tschisgale, Sophia Rauh, et al.
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