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X-ray image-based Radiology Report Generation (RRG) constitutes a critical research direction within medical artificial intelligence, with great potential to alleviate clinicians'diagnostic workload and shorten patient waiting periods. Despite substantial advances over recent years, the field faces evident bottlenecks...
This paper proposes a novel Multi-Agent Collaborative iterative framework for X-ray Radiology Report Generation, termed MAC-RRG, which constructs a closed-loop optimization paradigm based on task decoupling and collaborative reasoning.
This work proposes a novel multi-modal heat conduction operation framework for effective activity recognition, termed MMHCO-HAR, and conducts comprehensive experiments comparing the proposed method with baseline methods on the HARDVS 2.0 dataset and other public datasets.
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