Explainable Multi-Modal Deep Learning for Automatic Detection of Lung Diseases from Respiratory Audio Signals
Analysis
This article describes research on using explainable multi-modal deep learning to detect lung diseases from respiratory audio signals. The focus is on the explainability of the AI model, which is crucial for medical applications. The use of multi-modal data (likely combining audio with other data) suggests a potentially more robust and accurate diagnostic tool. The source, ArXiv, indicates this is a pre-print or research paper.
Key Takeaways
- •Focus on explainable AI for medical applications.
- •Utilizes multi-modal data for potentially improved accuracy.
- •Research paper published on ArXiv.
Reference
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