# Use of artificial intelligence for image analysis in breast cancer screening programmes: systematic review of test accuracy

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/use-of-artificial-intelligence-for-image-analysis-in-breast-cancer-screening/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Karoline Freeman,Julia Geppert,Chris Stinton,Daniel Todkill,Samantha Johnson,Aileen Clarke,Sian Taylor‐Phillips |
| Citations | 345 |
| DOI | 10.1136/bmj.n1872 |
| Fields | Computer Science,Medicine |
| Open Access | true |
| OA Status | hybrid |
| OA URL | https://www.bmj.com/content/bmj/374/bmj.n1872.full.pdf |
| OpenAlex ID | https://openalex.org/W3197840494 |
| PMID | 34470740 |
| Type | review |
| Year | 2021 |

## Paper authors

- [Aileen Clarke](https://scholariq.org/researchers/aileen-clarke/)

## Paper journal

- [BMJ](https://scholariq.org/journals/bmj-2/)

## 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/)
- [Artificial Intelligence in Healthcare and Education](https://scholariq.org/topics/artificial-intelligence-in-healthcare-and-education/)
- [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.