ArticleFrontiers in oncology2019
Glioblastoma and Anaplastic Astrocytoma: Differentiation Using MRI Texture Analysis.
Article in Frontiers in oncology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
13 citing papers in PubMed, 25 citations in OpenAlex.
- Stochastic differential equation modeling approach for grading astrocytomas on brain MRI images.Scientific reports · 2025Article
- Development of a nomogram based on radiomics and semantic features for predicting chromosome 7 gain/chromosome 10 loss in IDH wild-type histologically low-grade gliomas.Frontiers in oncology · 2023Article
- Machine learning and bioinformatics analysis to identify autophagy-related biomarkers in peripheral blood for rheumatoid arthritis.Frontiers in genetics · 2023Article
- The feasibility of MRI texture analysis in distinguishing glioblastoma, anaplastic astrocytoma and anaplastic oligodendroglioma.Translational cancer research · 2022Article
- Phantom Study on the Robustness of MR Radiomics Features: Comparing the Applicability of 3D Printed and Biological Phantoms.Diagnostics (Basel, Switzerland) · 2022Article
- Patients' Survival with Astrocytoma After Treatment: a Systematic Review and Meta-analysis of Clinical Trial Studies.Indian journal of surgical oncology · 2022Review
- Radiophysiomics: Brain Tumors Classification by Machine Learning and Physiological MRI Data.Cancers · 2022Article
- Differentiating Glioblastoma Multiforme from Brain Metastases Using Multidimensional Radiomics Features Derived from MRI and Multiple Machine Learning Models.BioMed research international · 2022Article
- Assessment of renal function using magnetic resonance quantitative histogram analysis based on spatial labeling with multiple inversion pulses.Annals of translational medicine · 2021Article
- Effect of grey-level discretization on texture feature on different weighted MRI images of diverse disease groups.PloS one · 2021Article
- Artificial intelligence for brain diseases: A systematic review.APL bioengineering · 2020Review
- Machine Learning Decision Tree Models for Differentiation of Posterior Fossa Tumors Using Diffusion Histogram Analysis and Structural MRI Findings.Frontiers in oncology · 2020Article
- Application of Radiomics Analysis Based on CT Combined With Machine Learning in Diagnostic of Pancreatic Neuroendocrine Tumors Patient's Pathological Grades.Frontiers in oncology · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
PubMed holds no abstract for this paper.
Indexed as
Identifiers
What OpenQuestion holds
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.