ReviewInsights into imaging2021
Clinical applications of artificial intelligence and radiomics in neuro-oncology imaging.
Review in Insights into imaging, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 66 papers, 2 of them syntheses that pooled it.
What it found
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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
66 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Using machine learning to predict remission after surgery for pituitary adenoma: a systematic review and meta-analysis.Endocrine · 2025Pooled it
- Current state of radiomics in pediatric neuro-oncology practice: a systematic review.Pediatric radiology · 2023Pooled it
- Article
- ChatNSG: An Overview of Contemporary and Emerging Artificial Intelligence Models for the Neurosurgeon.Journal of neurological surgery. Part B, Skull base · 2026Article
- Predicting the region of tumor micro-infiltration in glioblastoma peritumoral edema using a multiparametric mri radiomics model.Radiation oncology (London, England) · 2026Article
- A Novel Nomogram for Predicting Meningioma Grade Based on Radiomics Features and Clinical Characteristics.Current medical science · 2026Article
- Advancing Brain Tumor Diagnosis Using Deep Learning: A Systematic and Critical Review on Methodological Approaches to Glioma Segmentation and Classification Through Multiparametric MRI.Brain sciences · 2026Review
- BraTioUS: A multicenter dataset of baseline intraoperative brain tumor ultrasound images.Data in brief · 2026Article
- Current applications of radiomics in neurotrauma.Neurosurgical review · 2026Review
- Health economics evaluation of artificial intelligence in the field of oncology: a scoping review.Health economics review · 2026Review
- CT Radiomic Features of the Crystalline Lens and Association with Age, Hypertension and Cerebral White Matter Lesions.Diagnostics (Basel, Switzerland) · 2026Article
- Central Nervous System Involvement in Acute Myeloid Leukemia: From Pathophysiology to Neuroradiologic Features and the Emerging Role of Artificial Intelligence.Journal of clinical medicine · 2026Review
- Multimodal artificial intelligence in glioma management: integrating neuroimaging and hematologic biomarkers for precision oncology.Frontiers in oncology · 2026Review
- Advances in Preoperative and Intraoperative Technologies for Safe Resection of Gliomas in Cognitive Regions.Cancers · 2025Review
- Artificial intelligence in neuro-oncology: methodological bases, practical applications and ethical and regulatory issues.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2025Review
- Integrating deep learning and radiomics for preoperative glioma grading using multi-center MRI data.Scientific reports · 2025Article
- Predictive power of combined inflammatory markers and magnetic resonance imaging features for glioma grading using machine learning: a retrospective study.BMC medical imaging · 2025Article
- Radiomics in pediatric brain tumors: from images to insights.Discover oncology · 2025Review
- Advanced MRI, Radiomics and Radiogenomics in Unravelling Incidental Glioma Grading and Genetic Status: Where Are We?Medicina (Kaunas, Lithuania) · 2025Review
- A three-classification machine learning model for non-invasive prediction of molecular subtypes in diffuse glioma: a two-center study.Quantitative imaging in medicine and surgery · 2025Article
6 more citing papers are in PubMed but not listed here.
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.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This article is a comprehensive review of the basic background, technique, and clinical applications of artificial intelligence (AI) and radiomics in the field of neuro-oncology. A variety of AI and radiomics utilized conventional and advanced techniques to differentiate brain tumors from non-neoplastic lesions such as inflammatory and demyelinating brain lesions. It is used in the diagnosis of gliomas and discrimination of gliomas from lymphomas and metastasis. Also, semiautomated and automated tumor segmentation has been developed for radiotherapy planning and follow-up. It has a role in the grading, prediction of treatment response, and prognosis of gliomas. Radiogenomics allowed the connection of the imaging phenotype of the tumor to its molecular environment. In addition, AI is applied for the assessment of extra-axial brain tumors and pediatric tumors with high performance in tumor detection, classification, and stratification of patient's prognoses.
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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.