Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

Prediction of IDH1 Mutation Status in Glioblastoma Using Machine Learning Technique Based on Quantitative Radiomic Data

5 Feb 2019

Abstract excerpt

No abstract is available from the source.

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Cancer Genomics and Diagnostics
Share to Glioma Diagnosis and Treatment
Share to Radiomics and Machine Learning in Medical Imaging

Source

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Identifiers

PMID: 30735871
DOI: 10.1016/j.wneu.2019.01.157

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 6 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Prediction of IDH1 Mutation Status in Glioblastoma Using Machine Learning Technique Based on Quantitative Radiomic DataPMID 30735871Read ↗

Multicenter MRI Radiomics Features to Predict IHD1 Gene Mutation Status of Low-Grade GliomaSemantic proximity Read ↗

Detection of IDH1 mutation in human gliomas: comparison of immunohistochemistry and sequencingSemantic proximity Read ↗

From pixels to prognosis: leveraging radiomics and machine learning to predict IDH1 genotype in gliomas.Semantic proximity Read ↗

A radiomics model based on DCE-MRI and DWI may improve the prediction of estimating IDH1 mutation and angiogenesis in gliomas.Semantic proximity Read ↗

MRI Radiomic Features to Predict IDH1 Mutation Status in Gliomas: A Machine Learning Approach using Gradient Tree Boosting.Semantic proximity Read ↗

Noninvasive IDH1 mutation estimation based on a quantitative radiomics approach for grade II glioma.Semantic proximity Read ↗

Noninvasive prediction of IDH mutation status in gliomas using preoperative multiparametric MRI radiomics nomogram: A mutlicenter study.Semantic proximity Read ↗

A radiomics-clinical nomogram for preoperative prediction of IDH1 mutation in primary glioblastoma multiforme.Semantic proximity Read ↗

Competent Radiogenomics Features for the Prediction of glioma MutationsSemantic proximity Read ↗

Radiomics for Precision Medicine in GlioblastomaSemantic proximity Read ↗

Journal of Neuro Oncology: Diagnostic and therapeutic implications of IDH mutations in gliomas following the 2021 World Health Organization classification of CNS tumors.Semantic proximity Read ↗

Prognostic significance of IDH 1 mutation in patients with glioblastoma multiforme.Semantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.