• Corpus ID: 239616115

MHAttnSurv: Multi-Head Attention for Survival Prediction Using Whole-Slide Pathology Images

@article{Jiang2021MHAttnSurvMA,
  title={MHAttnSurv: Multi-Head Attention for Survival Prediction Using Whole-Slide Pathology Images},
  author={Shuai Jiang and Arief A. Suriawinata and Saeed Hassanpour},
  journal={ArXiv},
  year={2021},
  volume={abs/2110.11558}
}
In pathology, whole-slide images (WSI) based survival prediction has attracted increasing interest. However, given the large size of WSIs and the lack of pathologist annotations, extracting the prognostic information from WSIs remains a challenging task. Previous studies have used multiple instance learning approaches to combine the information from multiple randomly sampled patches, but different visual patterns may contribute differently to prognosis prediction. In this study, we developed a… 

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