ArticleCancers2023
MRI-Based Radiomics Combined with Deep Learning for Distinguishing IDH-Mutant WHO Grade 4 Astrocytomas from IDH-Wild-Type Glioblastomas.
Article in Cancers, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 2 of them syntheses that pooled it.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
19 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Radiomics-based artificial intelligence models in brain tumors: A systematic review and meta-analysis of diagnostic performance.Neuroradiology · 2026Pooled it
- Diagnostic performance of deep learning for predicting glioma isocitrate dehydrogenase and 1p/19q co-deletion in MRI: a systematic review and meta-analysis.European radiology · 2026Pooled it
- Functionally Informed Hand Knob Reveals Structural Connectome Differences in Motor-Eloquent Tumours.Cancers · 2026Article
- Isocitrate Dehydrogenase-Mutant Astrocytomas: Risk Stratification and Therapeutic Advance.MedComm · 2026Review
- A 3D feature fusion model integrating multi-scale MRI feature for interpretable Glioblastoma prediction.Medical & biological engineering & computing · 2026Article
- Foundation Model Based on Routine Magnetic Resonance Imaging for Brain Tumor Molecular Profiling and Progression Prediction.JCO precision oncology · 2026Article
- Cellularity habitat-based MRI radiomics for non-invasive grading and IDH mutation prediction in adult-type diffuse glioma.BMC medical imaging · 2026Article
- An approach for cancer outcomes modelling using a comprehensive synthetic dataset.Physical and engineering sciences in medicine · 2025Article
- Transforming 3D MRI to 2D Feature Maps Using Pre-Trained Models for Diagnosis of Attention Deficit Hyperactivity Disorder.Tomography (Ann Arbor, Mich.) · 2025Article
- Robust vs. Non-robust radiomic features: the quest for optimal machine learning models using phantom and clinical studies.Cancer imaging : the official publication of the International Cancer Imaging Society · 2025Article
- Development of Clinical-Radiomics Nomogram for Predicting Post-Surgery Functional Improvement in High-Grade Glioma Patients.Cancers · 2025Article
- Using partially shared radiomics features to simultaneously identify isocitrate dehydrogenase mutation status and epilepsy in glioma patients from MRI images.Scientific reports · 2025Article
- Predicting isocitrate dehydrogenase status in glioma using hierarchical attention-based deep 3D multiple instance learning.Frontiers in oncology · 2025Article
- Synthetic data generation methods in healthcare: A review on open-source tools and methods.Computational and structural biotechnology journal · 2024Review
- The effect of harmonization on the variability of PET radiomic features extracted using various segmentation methods.Annals of nuclear medicine · 2024Article
- Generative AI in glioma: Ensuring diversity in training image phenotypes to improve diagnostic performance for IDH mutation prediction.Neuro-oncology · 2024Article
- Time-to-event overall survival prediction in glioblastoma multiforme patients using magnetic resonance imaging radiomics.La Radiologia medica · 2023Article
- Novel insight into histological and molecular astrocytoma, IDH-mutant, Grade 4 by the updated WHO classification of central nervous system tumors.Cancer medicine · 2023Article
- Bridging the clinical gap: Confidence informed IDH prediction in brain gliomas using MRI and deep learning.Neuro-oncology advancesArticle
Corrections and comments
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Authors and funding
11 authors.
Funding
Abstract
This study aimed to investigate the potential of quantitative radiomic data extracted from conventional MR images in discriminating IDH-mutant grade 4 astrocytomas from IDH-wild-type glioblastomas (GBMs). A cohort of 57 treatment-naïve patients with IDH-mutant grade 4 astrocytomas (
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.