Back to search

Article

End-to-End Integrative Segmentation and Radiomics Prognostic Models Improve Risk Stratification of High-Grade Serous Ovarian Cancer: A Retrospective Multi-Cohort Study

2023-04-28

Abstract excerpt

<h4>Summary</h4> <h4>Background</h4> Valid stratification factors for patients with epithelial ovarian cancer (EOC) are still lacking and individualisation of care remains an unmet need. Radiomics from routine Contrast Enhanced Computed Tomography (CE-CT) is an emerging, highly promising approach towards more accurate prognostic models for the better preoperative stratification of the subset of patients with hig...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work
46589356-8884-5efc-970b-12bc319394a0
DOI
10.1101/2023.04.26.23289155
Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest
Interactive article relationship graphSelect a related publication card to move it into the centre and load its closest explainable connections. Solid lines are source-backed structured connections. Dashed lines are semantic discovery signals and are not scientific evidence.
End-to-End Integrative Segmentation and Radiomics Prognostic Models Improve Risk Stratification of High-Grade Serous Ovarian Cancer: A Retrospective Multi-Cohort StudyDOI 10.1101/2023.04.26.23289155
Select a neighboring publication to make it the new centre.