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Frontiers in Artificial Intelligence|October 29, 2026
Landscape and training opportunities in artificial intelligence for biosciences in Latin America: the BiotrAIn projectJose Arturo Molina-Mora, Flavio Ezequiel Spetale, Tulio de Lima Campos, et al.
Frontiers in Artificial Intelligence|November 3, 2026
Data-based surrogate modeling and performance prediction of MEMS touch mode capacitive sensing using deep multilayer perceptron networksPushparaj E, Sumit Kumar Jindal
Frontiers in Artificial Intelligence|November 3, 2026
AFI-ID: adaptive feature intelligence for intrusion detectionS Antony Joseph Raj, M Madiajagan
Frontiers in Artificial Intelligence|November 4, 2026
Physics-inspired feature engineering and explainable machine learning for tensile strength prediction of CNT-Si₃N₄ reinforced FWTPET jointsKrishnan Venkatachalam, Senthil Kumaran Selvaraj, R Lokeshkumar, et al.
Frontiers in Artificial Intelligence|November 4, 2026
Mammography datasets and artificial intelligence for breast cancer detection: challenges, bias, and future directionsA Kaja Mohideen, P N Senthil Prakash, M K Priyadharshini
Frontiers in Artificial Intelligence|November 5, 2026
The AI incident disclosure shadow: tracking AI incidents into U.S. securities filingsSamir Chincholikar, Robin Chawla
Frontiers in Artificial Intelligence|November 5, 2026
TongueBench: performance of prompt-engineered large multimodal models in Traditional Chinese Medicine tongue diagnosisYihan Meng, Nuan Cui, Jingxin Yao, et al.
Frontiers in Artificial Intelligence|January 5, 2026
Machine learning-guided clinical pharmacist interventions improve treatment outcomes in tuberculosis patients: a precision medicine approachDang Yi, Huanqing Liu, Qian Lei, et al.
Frontiers in Artificial Intelligence|January 5, 2026
Retrieving interpretability to support vector machine regression models in dynamic system identificationJohan Pena-Campos, Diego Patino, Carlos Ocampo-Martinez, et al.
Frontiers in Artificial Intelligence|January 5, 2026
Development and validation of a multi-agent AI pipeline for automated credibility assessment of tobacco misinformation: a proof-of-concept studySherif Elmitwalli, John Mehegan, Sophie Braznell, et al.
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