# The application of deep learning based diagnostic system to cervical squamous intraepithelial lesions recognition in colposcopy images

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/the-application-of-deep-learning-based-diagnostic-system-to-cervical-squamous/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Chunnv Yuan,Yeli Yao,Bei Cheng,Yifan Cheng,Ying Li,Yang Li,Xuechen Liu,Xiaodong Cheng,Xing Xie,Jian Wu,Xinyu Wang,Weiguo Lü |
| Citations | 214 |
| DOI | 10.1038/s41598-020-68252-3 |
| Fields | Computer Science,Medicine |
| Open Access | true |
| OA Status | gold |
| OA URL | https://www.nature.com/articles/s41598-020-68252-3.pdf |
| OpenAlex ID | https://openalex.org/W3043279728 |
| PMID | 32669565 |
| Type | article |
| Year | 2020 |

## Paper authors

- [Weiguo Lü](https://scholariq.org/researchers/weiguo-lu/)

## Paper journal

- [Scientific Reports](https://scholariq.org/journals/scientific-reports/)

## Paper primary topic

- [Cervical Cancer and HPV Research](https://scholariq.org/topics/cervical-cancer-and-hpv-research/)

## Paper topics

- [Cervical Cancer and HPV Research](https://scholariq.org/topics/cervical-cancer-and-hpv-research/)
- [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/)

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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.