Resp-Agent: Revolutionizing Respiratory Diagnosis with AI!
research#agent🔬 Research|Analyzed: Feb 19, 2026 05:04•
Published: Feb 19, 2026 05:00
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Resp-Agent is an exciting new system that leverages the power of Generative AI and Agents to tackle challenges in respiratory sound analysis. Its innovative Active Adversarial Curriculum Agent, Thinker-A$^2$CA, dynamically adapts to improve diagnostic accuracy, opening doors for more robust and reliable disease detection.
Key Takeaways
- •Resp-Agent uses an Agent-based system for multimodal respiratory sound generation and disease diagnosis.
- •The system employs a novel Active Adversarial Curriculum Agent (Thinker-A$^2$CA) for dynamic improvement.
- •Resp-Agent outperforms previous methods across evaluation settings, enhancing diagnostic reliability.
Reference / Citation
View Original"Extensive experiments demonstrate that Resp-Agent consistently outperforms prior approaches across diverse evaluation settings, improving diagnostic robustness under data scarcity and long-tailed class imba"