# Pathologist-level interpretable whole-slide cancer diagnosis with deep learning

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/pathologist-level-interpretable-whole-slide-cancer-diagnosis-with-deep-learning/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Zizhao Zhang,Pingjun Chen,Mason McGough,Fuyong Xing,Chunbao Wang,Marilyn M. Bui,Yuanpu Xie,Manish Sapkota,Lei Cui,Jasreman Dhillon,Nazeel Ahmad,Farah Khalil,Shohreh Dickinson,Xiaoshuang Shi,Fujun Liu,Hai Su,Jinzheng Cai,Lin Yang |
| Citations | 322 |
| DOI | 10.1038/s42256-019-0052-1 |
| Fields | Computer Science,Medicine |
| Open Access | false |
| OA Status | closed |
| OpenAlex ID | https://openalex.org/W2945807221 |
| Type | article |
| Year | 2019 |

## Paper authors

- [Chunbao Wang](https://scholariq.org/researchers/chunbao-wang/)

## Paper primary topic

- [AI in cancer detection](https://scholariq.org/topics/ai-in-cancer-detection/)

## Paper topics

- [AI in cancer detection](https://scholariq.org/topics/ai-in-cancer-detection/)
- [Colorectal Cancer Screening and Detection](https://scholariq.org/topics/colorectal-cancer-screening-and-detection/)
- [Radiomics and Machine Learning in Medical Imaging](https://scholariq.org/topics/radiomics-and-machine-learning-in-medical-imaging/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.