A systematic evaluation of CL for MedVQA across diverse clinical objectives, including classification, multi-label classification, detection, cell counting, and report generation suggests that existing CL methods struggle to maintain stability-plasticity balance when tasks with different objectives and supervision form...
Mai A. Shaaban, Tausifa Jan Saleem, Alaa Mohamed et al.· arXiv.org· 0 citations
A novel multimodal RAG framework tailored for MedVQA is proposed, which leverages multimodal data, including medical images, reports, and generated captions, to provide more accurate clinical answers, and introduces a training paradigm that uses captions as auxiliary supervision, enhancing cross-modal alignment via con...
Mai A. Shaaban, M. Zarei, Adnan Khan et al.· 0 citations
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