Robust Machine Learning Techniques Accurately Predict Genotype Using Magnetic Resonance Radiomic Data: A Multicentric Pooled Analysis of 263 Glioma Patients (P4-6.001)

To explore the potential of radiomics as a non-invasive diagnostic tool to predict 1p/19q co-deletion status, IDH mutant genotype, and MGMT promoter methylation.

Authors

Suhrud Panchawagh (ORCID: https://orcid.org/0000-0002-8606-4202)

Publication Details

Journal: Neurology
Published: 2025-04-07
DOI: https://doi.org/10.1212/wnl.0000000000208531
Primary Topic: Radiomics and Machine Learning in Medical Imaging
Type: article
Field-Weighted Citation Impact: 0.00

Controls

|||

ALL TIME

JAN

FEB

MAR

APR

MAY

JUN

JUL

AUG

SEP

OCT

article

Robust Machine Learning Techniques Accurately Predict Genotype Using Magnetic Resonance Radiomic Data: A Multicentric Pooled Analysis of 263 Glioma Patients (P4-6.001)

Suhrud Panchawagh

Apr 7, 2025

Neurology

Radiomics and Machine Learning in Medical Imaging

article

Robust Machine Learning Techniques Accurately Predict Genotype Using Magnetic Resonance Radiomic Data: A Multicentric Pooled Analysis of 263 Glioma Patients (P4-6.001)

Suhrud Panchawagh

April 7, 2025article en

Abstract

To explore the potential of radiomics as a non-invasive diagnostic tool to predict 1p/19q co-deletion status, IDH mutant genotype, and MGMT promoter methylation.

NeurologyVol. 104(7_Supplement_1)

Openalex Percentile: Top 89%

Radiomics and Machine Learning in Medical Imaging

DOI Source OpenAlex

AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Robust Machine Learning Techniques Accurately Predict Genotype Using Magnetic Resonance Radiomic Data: A Multicentric Pooled Analysis of 263 Glioma Patients (P4-6.001) — Suhrud Panchawagh · Neurology (2025) | TGRS Research Map | TGRS