# A deep look into radiomics

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/a-deep-look-into-radiomics/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Camilla Scapicchio,Michela Gabelloni,Andrea Barucci,Dania Cioni,Luca Saba,Emanuele Neri |
| Citations | 424 |
| DOI | 10.1007/s11547-021-01389-x |
| Fields | Computer Science,Engineering,Medicine |
| Open Access | true |
| OA Status | hybrid |
| OA URL | https://link.springer.com/content/pdf/10.1007/s11547-021-01389-x.pdf |
| OpenAlex ID | https://openalex.org/W3175762528 |
| PMID | 34213702 |
| Type | article |
| Year | 2021 |

## Paper authors

- [Luca Saba](https://scholariq.org/researchers/luca-saba/)

## Paper primary topic

- [Radiomics and Machine Learning in Medical Imaging](https://scholariq.org/topics/radiomics-and-machine-learning-in-medical-imaging/)

## Paper topics

- [Radiomics and Machine Learning in Medical Imaging](https://scholariq.org/topics/radiomics-and-machine-learning-in-medical-imaging/)
- [Advanced X-ray and CT Imaging](https://scholariq.org/topics/advanced-x-ray-and-ct-imaging/)
- [AI in cancer detection](https://scholariq.org/topics/ai-in-cancer-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.