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Predicting Human Emotions using EEG-based Brain computer Interface and Interpretable Machine Learning., , , , и . Ital-IA, том 3486 из CEUR Workshop Proceedings, стр. 200-205. CEUR-WS.org, (2023)Combining Mental States Recognition and Machine Learning for Neurorehabilitation., , , , , и . SMC, стр. 3848-3853. IEEE, (2023)Brain Computer Interface, Visual Tracker and Artificial Intelligence for a Music Polyphony Generation System., , , и . INTERACT (5), том 12936 из Lecture Notes in Computer Science, стр. 368-371. Springer, (2021)MAFUS: a Framework to predict mortality risk in MAFLD subjects., , , , , , и . CoRR, (2023)A Pareto-Optimality-Based Approach for Selecting the Best Machine Learning Models in Mild Cognitive Impairment Prediction., , , , , , , и . SMC, стр. 3822-3827. IEEE, (2023)Brain Computer Interface: Deep Learning Approach to Predict Human Emotion Recognition., , , , , , , , и . SMC, стр. 2689-2694. IEEE, (2022)Exploring the Mental State Intersection by Brain-Computer Interfaces, Cellular Automata and Biofeedback., , , , , и . EUROCON, стр. 461-466. IEEE, (2023)Time-to-Event Interpretable Machine Learning for Multiple Sclerosis Worsening Prediction: Results from iDPP@CLEF 2023., , , , , , , , , и . CLEF (Working Notes), том 3497 из CEUR Workshop Proceedings, стр. 1272-1285. CEUR-WS.org, (2023)A Biofeedback System to Compose Your Own Music While Dancing., , , и . INTERACT (5), том 12936 из Lecture Notes in Computer Science, стр. 309-312. Springer, (2021)NeuralPMG: A Neural Polyphonic Music Generation System Based on Machine Learning Algorithms., , , , , , и . Cogn. Comput., 16 (5): 2779-2802 (сентября 2024)