# A semi-supervised multi-task learning framework for cancer classification with weak annotation in whole-slide images

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/a-semi-supervised-multi-task-learning-framework-for-cancer-classification-with/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Zeyu Gao,Bangyang Hong,Yang Li,Xianli Zhang,Jialun Wu,Chunbao Wang,Xiangrong Zhang,Tieliang Gong,Yefeng Zheng,Deyu Meng,Chen Li |
| Citations | 70 |
| DOI | 10.1016/j.media.2022.102652 |
| Fields | Computer Science,Medicine |
| Open Access | false |
| OA Status | closed |
| OpenAlex ID | https://openalex.org/W4306250152 |
| PMID | 36327654 |
| Type | article |
| Year | 2022 |

## 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/)
- [Radiomics and Machine Learning in Medical Imaging](https://scholariq.org/topics/radiomics-and-machine-learning-in-medical-imaging/)
- [Digital Imaging for Blood Diseases](https://scholariq.org/topics/digital-imaging-for-blood-diseases/)

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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.