# Combination of Radiomics and Machine Learning with Diffusion-Weighted MR Imaging for Clinical Outcome Prognostication in Cervical Cancer

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/combination-of-radiomics-and-machine-learning-with-diffusion-weighted-mr-imaging/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Ankush Jajodia,Ayushi Gupta,Helmut Prosch,Marius E. Mayerhoefer,Swarupa Mitra,Sunil Pasricha,Anurag Mehta,Sunil Puri,Arvind Chaturvedi |
| Citations | 30 |
| DOI | 10.3390/tomography7030031 |
| Fields | Medicine |
| Open Access | true |
| OA Status | gold |
| OA URL | https://www.mdpi.com/2379-139X/7/3/31/pdf?version=1628150113 |
| OpenAlex ID | https://openalex.org/W3174918489 |
| PMID | 34449713 |
| Type | article |
| Year | 2021 |

## Paper authors

- [Sunil Pasricha](https://scholariq.org/researchers/sunil-pasricha/)

## Paper primary topic

- [Endometrial and Cervical Cancer Treatments](https://scholariq.org/topics/endometrial-and-cervical-cancer-treatments/)

## Paper topics

- [Endometrial and Cervical Cancer Treatments](https://scholariq.org/topics/endometrial-and-cervical-cancer-treatments/)
- [Radiomics and Machine Learning in Medical Imaging](https://scholariq.org/topics/radiomics-and-machine-learning-in-medical-imaging/)
- [MRI in cancer diagnosis](https://scholariq.org/topics/mri-in-cancer-diagnosis/)

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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.