Multimodal optimal transport-based co-attention transformer with global structure consistency for survival prediction
Survival prediction is a complicated ordinal regression task that aims to predict the ranking
risk of death, which generally benefits from the integration of histology and genomic data …
risk of death, which generally benefits from the integration of histology and genomic data …
Modeling dense multimodal interactions between biological pathways and histology for survival prediction
Integrating whole-slide images (WSIs) and bulk transcriptomics for predicting patient survival
can improve our understanding of patient prognosis. However this multimodal task is …
can improve our understanding of patient prognosis. However this multimodal task is …
Hierarchical transformer for survival prediction using multimodality whole slide images and genomics
Learning good representation of giga-pixel level whole slide pathology images (WSI) for
downstream tasks is critical. Previous studies employ multiple instance learning (MIL) to …
downstream tasks is critical. Previous studies employ multiple instance learning (MIL) to …
Hvtsurv: Hierarchical vision transformer for patient-level survival prediction from whole slide image
Survival prediction based on whole slide images (WSIs) is a challenging task for patient-
level multiple instance learning (MIL). Due to the vast amount of data for a patient (one or …
level multiple instance learning (MIL). Due to the vast amount of data for a patient (one or …
Multimodal co-attention transformer for survival prediction in gigapixel whole slide images
Survival outcome prediction is a challenging weakly-supervised and ordinal regression task
in computational pathology that involves modeling complex interactions within the tumor …
in computational pathology that involves modeling complex interactions within the tumor …
TransSurv: transformer-based survival analysis model integrating histopathological images and genomic data for colorectal cancer
Survival analysis is a significant study in cancer prognosis, and the multi-modal data,
including histopathological images, genomic data, and clinical information, provides …
including histopathological images, genomic data, and clinical information, provides …
Survival prediction via hierarchical multimodal co-attention transformer: A computational histology-radiology solution
The rapid advances in deep learning-based computational pathology and radiology have
demonstrated the promise of using whole slide images (WSIs) and radiology images for …
demonstrated the promise of using whole slide images (WSIs) and radiology images for …
[HTML][HTML] Surformer: An interpretable pattern-perceptive survival transformer for cancer survival prediction from histopathology whole slide images
Z Wang, Q Gao, X Yi, X Zhang, Y Zhang… - Computer Methods and …, 2023 - Elsevier
Abstract Background and Objective High-resolution histopathology whole slide images
(WSIs) contain abundant valuable information for cancer prognosis. However, most …
(WSIs) contain abundant valuable information for cancer prognosis. However, most …
CAMR: cross-aligned multimodal representation learning for cancer survival prediction
Motivation Accurately predicting cancer survival is crucial for helping clinicians to plan
appropriate treatments, which largely improves the life quality of cancer patients and spares …
appropriate treatments, which largely improves the life quality of cancer patients and spares …
Pathology-and-genomics multimodal transformer for survival outcome prediction
Survival outcome assessment is challenging and inherently associated with multiple clinical
factors (eg, imaging and genomics biomarkers) in cancer. Enabling multimodal analytics …
factors (eg, imaging and genomics biomarkers) in cancer. Enabling multimodal analytics …