Corpus ID: 209414717

Pathomic Fusion: An Integrated Framework for Fusing Histopathology and Genomic Features for Cancer Diagnosis and Prognosis

@article{Chen2019PathomicFA,
  title={Pathomic Fusion: An Integrated Framework for Fusing Histopathology and Genomic Features for Cancer Diagnosis and Prognosis},
  author={Richard J. Chen and Ming Yu Lu and Junling Wang and Drew F. K. Williamson and Scott J. Rodig and Neal I. Lindeman and F. Mahmood},
  journal={ArXiv},
  year={2019},
  volume={abs/1912.08937}
}
  • Richard J. Chen, Ming Yu Lu, +4 authors F. Mahmood
  • Published 2019
  • Computer Science, Biology
  • ArXiv
  • Cancer diagnosis, prognosis, and therapeutic response predictions are based on morphological information from histology slides and molecular profiles from genomic data. However, most deep learning-based objective outcome prediction and grading paradigms are based on histology or genomics alone and do not make use of the complementary information in an intuitive manner. In this work, we propose Pathomic Fusion, a strategy for end-to-end multimodal fusion of histology image and genomic (mutations… CONTINUE READING

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