REN: Anatomically-Informed Mixture-of-Experts for Interstitial Lung Disease Diagnosis
REN:基于解剖学的专家混合模型用于间质性肺病诊断
机构 * Department of Computer Science, Northwestern University McCormick School of Engineering and Applied Science(西北大学麦考密克工程与应用科学学院计算机科学系) ; Division of Pulmonary and Critical Care Medicine, Northwestern University Feinberg School of Medicine(西北大学范伯格医学院肺与危重症医学科) ; Division of Rheumatology, Northwestern University Feinberg School of Medicine(西北大学范伯格医学院风湿病科) ; Simpson Querrey Lung Institute for Translational Science, Northwestern University Feinberg School of Medicine(西北大学范伯格医学院辛普森·奎雷转化科学肺研究所) ; Department of Electrical and Computer Engineering, Northwestern University McCormick School of Engineering and Applied Science(西北大学麦考密克工程与应用科学学院电气与计算机工程系) ; Machine & Hybrid Intelligence Lab, Department of Radiology, Northwestern University Feinberg School of Medicine(西北大学范伯格医学院放射科机器与混合智能实验室)
专题命中 诊断辅助 :diagnosis(title);medical image(abstract);分类 cs.CV
AI总结 本文提出REN模型,通过解剖学指导的专家混合框架提升间质性肺病诊断性能,结合多模态门控机制和深度学习特征,实现更精确的病理变化建模。
Comments 13 pages, 4 figures, 5 tables