Back to search

Article

Value of contrast-enhanced CT based radiomic machine learning algorithm in differentiating gastrointestinal stromal tumors with KIT exon 11 mutation: a two-center study

2020-08-04

Abstract excerpt

<title>Abstract</title> <p><bold>Background </bold>Knowing the genetic phenotype of gastrointestinal stromal tumors (GISTs) is essential for patients who receive therapy with tyrosine kinase inhibitors.<bold>Methods </bold>We enrolled 106 patients (80 in the training set, 26 in the validation set) with clinicopathologically confirmed GISTs from two centers. Preoperative and postoperative clinical characteristics...

Topics

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

Identifiers and source

Literature Corpus work
7d3055a7-648b-55e7-9561-92f7c7be73a1
DOI
10.21203/rs.3.rs-48361/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.
Value of contrast-enhanced CT based radiomic machine learning algorithm in differentiating gastrointestinal stromal tumors with KIT exon 11 mutation: a two-center studyDOI 10.21203/rs.3.rs-48361/v1
Value of contrast-enhanced CT based radiomic machine learning algorithm in differentiating gastrointestinal stromal tumors with KIT exon 11 mutation: a two-center study.Semantic proximity
Predictive Value of a Radiomics Nomogram Model Based on Contrast-Enhanced Computed Tomography for KIT Exon 9 Gene Mutation in Gastrointestinal Stromal Tumors.Semantic proximity
Personalized radiomics signature to screen for KIT-11 mutation genotypes among patients with gastrointestinal stromal tumors: a retrospective multicenter study.Semantic proximity
Gastrointestinal stromal tumors: associations between contrast-enhanced CT images and KIT exon 11 gene mutationSemantic proximity
Application of CT Radiomics Combined with Machine Learning Methods in Predicting the Recurrence or Metastasis of Gastrointestinal Stromal TumorsSemantic proximity
Identification of D842V mutation in gastrointestinal stromal tumors based on CT radiomics: a multi-center study.Semantic proximity
Preoperative prediction of KRAS mutation status in colorectal cancer using a CT-based radiomics nomogram.Semantic proximity
CT Radiogenomics for Differentiating KIT Exon 11 from non-KIT Exon 11 Gene Mutations in Small Intestinal Gastrointestinal Stromal TumorsSemantic proximity
MRI T2WI-based radiomics combined with KRAS gene mutation constructed models for predicting liver metastasis in rectal cancer.Semantic proximity
Study on the Combined Prediction Model of c-KIT and PDGFRa Gene Mutation Status and Clinicopathological Features in 241 Patients with Gastrointestinal Stromal TumorsSemantic proximity
A computed tomography-based radiomics prediction model for BRAF mutation status in colorectal cancer.Semantic proximity
Prediction of Mutations and Outcome in Gastrointestinal Stromal Tumors with Deep Learning: A Multicenter, Multinational StudySemantic proximity
Select a neighboring publication to make it the new centre.