ReXplain：将放射学报告转化为患者友好的视频报告
ReXplain: Translating Radiology into Patient-Friendly Video Reports
AI总结：
针对放射报告难懂的问题，ReXplain系统集成大语言模型、图像分割和虚拟形象生成，将放射学发现转化为患者友好的视频报告，经放射科医生评估，能准确传递信息并模拟一对一咨询，提升患者参与度。
摘要：
放射学报告旨在促进医学专家之间的高效沟通，但患者往往难以理解。这种不可及性可能导致焦虑、降低患者对治疗决策的参与度，并导致较差的健康结果，从而削弱以患者为中心的护理。我们提出了ReXplain（放射学解释系统），一个创新的AI驱动系统，可将放射学发现转化为患者友好的视频报告。ReXplain独特地集成了用于医学文本简化和文本-解剖关联的大型语言模型、用于解剖区域识别的图像分割模型，以及用于交互式界面可视化的虚拟形象生成工具。ReXplain能够以视频报告的形式，用通俗语言、高亮图像和3D器官渲染生成全面的解释。为评估ReXplain生成解释的实用性，我们进行了两轮来自六位委员会认证放射科医生的用户反馈收集。这项概念验证研究的结果表明，ReXplain能够准确传递放射学信息，并有效模拟一对一咨询，为增强以患者为中心的放射学并具有潜在临床应用价值提供了启示。这项工作展示了AI辅助医学沟通的新范式，可能改善放射护理中患者的参与度和满意度，并为多模态医学沟通研究开辟了新途径。
英文摘要：
Radiology reports, designed for efficient communication between medical experts, often remain incomprehensible to patients. This inaccessibility could potentially lead to anxiety, decreased engagement in treatment decisions, and poorer health outcomes, undermining patient-centered care. We present ReXplain (Radiology eXplanation), an innovative AI-driven system that translates radiology findings into patient-friendly video reports. ReXplain uniquely integrates a large language model for medical text simplification and text-anatomy association, an image segmentation model for anatomical region identification, and an avatar generation tool for engaging interface visualization. ReXplain enables producing comprehensive explanations with plain language, highlighted imagery, and 3D organ renderings in the form of video reports. To evaluate the utility of ReXplain-generated explanations, we conducted two rounds of user feedback collection from six board-certified radiologists. The results of this proof-of-concept study indicate that ReXplain could accurately deliver radiological information and effectively simulate one-on-one consultation, shedding light on enhancing patient-centered radiology with potential clinical usage. This work demonstrates a new paradigm in AI-assisted medical communication, potentially improving patient engagement and satisfaction in radiology care, and opens new avenues for research in multimodal medical communication.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
