
A breast cancer tumor classification model. This model is a ResNet34 and was trained on TCGA BRCA.

Please refer to the [original GitHub Repo](https://github.com/SBU-BMI/quip_cancer_segmentation) 
and the [associated paper](https://pubmed.ncbi.nlm.nih.gov/32277893/). If you find this model useful,
please consider citing relevant paper:

```bibtex
@article{le2020utilizing,
  title={Utilizing automated breast cancer detection to identify spatial distributions of tumor-infiltrating lymphocytes in invasive breast cancer},
  author={Le, Han and Gupta, Rajarsi and Hou, Le and Abousamra, Shahira and Fassler, Danielle and Torre-Healy, Luke and Moffitt, Richard A and Kurc, Tahsin and Samaras, Dimitris and Batiste, Rebecca and others},
  journal={The American journal of pathology},
  volume={190},
  number={7},
  pages={1491--1504},
  year={2020},
  publisher={Elsevier}
}
```
{"license": "cc-by-4.0", "library_name": "pytorch"}
pytorch safetensors license:cc-by-4.0 region:us
TAGS
#pytorch #safetensors #license-cc-by-4.0 #region-us 


A breast cancer tumor classification model. This model is a ResNet34 and was trained on TCGA BRCA.

Please refer to the original GitHub Repo 
and the associated paper. If you find this model useful,
please consider citing relevant paper:


TAGS
#pytorch #safetensors #license-cc-by-4.0 #region-us 
