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pro vyhledávání: '"Toikkanen, Miika"'
Respiratory sound classification (RSC) is challenging due to varied acoustic signatures, primarily influenced by patient demographics and recording environments. To address this issue, we introduce a text-audio multimodal model that utilizes metadata
Externí odkaz:
http://arxiv.org/abs/2406.06786
Recent advancements in AI have democratized its deployment as a healthcare assistant. While pretrained models from large-scale visual and audio datasets have demonstrably generalized to this task, surprisingly, no studies have explored pretrained spe
Externí odkaz:
http://arxiv.org/abs/2405.02996
Deep generative models have emerged as a promising approach in the medical image domain to address data scarcity. However, their use for sequential data like respiratory sounds is less explored. In this work, we propose a straightforward approach to
Externí odkaz:
http://arxiv.org/abs/2311.06480