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A Generative Foundation Model for Multimodal Histopathology
Jinxi Xiang, Mingjie Li, Siyu Hou +9
Accurate diagnosis and treatment of complex diseases require integrating histological, molecular, and clinical data, yet in practice these modalities are often incomplete owing to…
nnMIL: A generalizable multiple instance learning framework for computational pathology
Xiangde Luo, Jinxi Xiang, Yuanfeng Ji +1
Computational pathology holds substantial promise for improving diagnosis and guiding treatment decisions. Recent pathology foundation models enable the extraction of rich patch-le…
A Generative Foundation Model for Chest Radiography
Yuanfeng Ji, Dan Lin, Xiyue Wang +12
The scarcity of well-annotated diverse medical images is a major hurdle for developing reliable AI models in healthcare. Substantial technical advances have been made in generative…
Ensemble learning of pathology foundation models for precision oncology
Xiangde Luo, Xiyue Wang, Feyisope Eweje +24
Histopathology is essential for cancer diagnosis and treatment selection, and pathology foundation models learn visual representations from whole-slide images (WSIs). However, exis…