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However, by simply utilizing textual information and ignoring other modal details such as images, LLMs fail to achieve high accuracy in the early diagnosis of breast cancer and thus have not yet been seamlessly integrated into the clinical practice of breast cancer diagnosis. Therefore, this study proposes that the Parallel Multimodal Language Model (PMLM) combines images and text, integrates visual and semantic information in text for early screening and diagnosis of breast cancer, and improves the accuracy of early screening and diagnosis, while also enhancing health system access. In addition, existing multimodal diagnostic methods are evaluated. 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