Back to search

Article

Preoperative contrast-enhanced CT-based deep learning radiomics model for distinguishing retroperitoneal lipomas and well‑differentiated liposarcomas

2024-03-05

Abstract excerpt

<title>Abstract</title> <p><bold>Objectives </bold>To assess the efficacy of a preoperative contrast-enhanced CT (CECT) –based deep learning radiomics nomogram (DLRN) for predicting murine double minute 2 (MDM2) gene amplification as a means of distinguishing between retroperitoneal well-differentiated liposarcomas (WDLPS) and lipomas. <bold>Methods </bold>This retrospective multi-centre study included 167 patien...

Topics

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

Identifiers and source

Literature Corpus work
bdcf05e7-f0ac-5337-a568-1b6c3dedc5fb
DOI
10.21203/rs.3.rs-3999164/v1
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.
Preoperative contrast-enhanced CT-based deep learning radiomics model for distinguishing retroperitoneal lipomas and well‑differentiated liposarcomasDOI 10.21203/rs.3.rs-3999164/v1
Machine learning-based radiomics model for accurately predicting subtypes of neuroblastoma in children: A retrospective analysisSemantic proximity
Update on genomic and molecular landscapes of well-differentiated liposarcoma and dedifferentiated liposarcoma.Semantic proximity
CT-Based Radiomics and Machine Learning for Differentiating Benign, Borderline, and Early-stage Malignant Ovarian Tumors: A Multi-Class Classification and Multi-Model Comparation StudySemantic proximity
Value of contrast-enhanced CT based radiomic machine learning algorithm in differentiating gastrointestinal stromal tumors with KIT exon 11 mutation: a two-center studySemantic proximity
Non-invasive Radiomics Model for Preoperative Prediction of Dual-phenotype Hepatocellular Carcinoma Based on CT DataSemantic proximity
Molecular Feature-Based Classification of Retroperitoneal Liposarcoma: A Prospective Cohort StudySemantic proximity
Development and Validation of a CEUS-Based Intratumoral–Peritumoral Radiomics Nomogram for Preoperative Prediction of HER2-Low Breast CancerSemantic proximity
A CT-based Deep Learning Radiomics Nomogram for the Prediction of EGFR Mutation Status in Head and Neck Squamous Cell Carcinoma.Semantic proximity
Radiomics Features Predict Telomerase Reverse Transcriptase Promoter Mutations in World Health Organization Grade II Gliomas via a Machine-Learning ApproachSemantic proximity
Multiparametric MRI-based radiomics combined with machine learning for preoperative differentiation of luminal A and luminal B breast cancer: a multicenter studySemantic proximity
Development and validation of a prognostic nomogram for predicting overall survival in patients with large retroperitoneal liposarcoma: a population-based cohort studySemantic proximity
Machine learning–based 18F-FDG PET/MR fusion radiomics for predicting EGFR mutation in lung cancerSemantic proximity
Select a neighboring publication to make it the new centre.