Researchers have proposed a unifying mathematical framework that helps explain why many successful multimodal AI systems work ...
1 Department of Computer Science, Western University, London, ON, Canada 2 Department of Biochemistry, Western University, London, ON, Canada This repository contains the code, datasets, and trained ...
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Bipolar Disorder, Digital Phenotyping, Multimodal Learning, Face/Voice/Phone, Mood Classification, Relapse Prediction, T-SNE, Ablation Share and Cite: de Filippis, R. and Al Foysal, A. (2025) ...
Abstract: Cell-Free massive MIMO (CF-mMIMO) is a promising technology for enabling Federated Learning (FL) in the next generation of wireless networks due to its uniform service coverage. However, ...
Abstract: As medical images from multiple modalities provide complementary diagnostic information, multimodal medical image classification (MMIC) leverages their integration to enhance disease ...
Introduction: Physiological signals offer a significant advantage in the field of emotion recognition due to their objective nature, as they are less susceptible to volitional control and thus provide ...
The convergence of digital transformation and the GenAI revolution creates an unprecedented opportunity for accelerating progress in precision health. Precision immunotherapy is a poster child for ...