ReviewNPJ precision oncology2024
Artificial intelligence in neuro-oncology: advances and challenges in brain tumor diagnosis, prognosis, and precision treatment.
Review in NPJ precision oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 114 papers, 5 of them syntheses that pooled it.
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
114 citing papers in PubMed, 5 syntheses or guidelines pooled it.
- Systematic Review of Artificial Intelligence Applications in Clinical Trials for Central Nervous System Injuries.Current neuropharmacology · 2026Pooled it
- Advances in AI-Driven EEG Analysis for Neurological and Oculomotor Disorders: A Systematic Review.Biosensors · 2025Pooled it
- Artificial intelligence and machine learning driven segmentation and quantification models for brain arteriovenous malformations: A systematic review.Neuroradiology · 2025Pooled it
- Exploring the role of artificial intelligence in chemotherapy development, cancer diagnosis, and treatment: present achievements and future outlook.Frontiers in oncology · 2025Pooled it
- The effects of artificial intelligence on human resource activities and the roles of the human resource triad: opportunities and challenges.Frontiers in psychology · 2024Pooled it
- A class-wise quantum relational calibration network for brain tumor diagnosis.Scientific reports · 2026Article
- Applications of Artificial Intelligence in Cancer Diagnosis and Treatment.Cancer medicine · 2026Review
- Dual modal pathomics model for colorectal cancer early recurrence prediction and mutation landscape analysis.iScience · 2026Article
- Integrating Endovascular Drug Delivery into the Therapeutic Landscape of Glioblastoma.Cancers · 2026Review
- Advanced Deep Learning Architectures in MRI-Based Brain Tumor Classification: A Systematic Review Focused on Meningiomas.Journal of imaging informatics in medicine · 2026Review
- Supramaximal resection in gliomas: a narrative review of surgical techniques, clinical outcomes, and ethical considerations.Annals of medicine and surgery (2012) · 2026Review
- A multi-modal foundation model for brain disease diagnosis and medical imaging.Patterns (New York, N.Y.) · 2026Article
- Lightweight Transfer Learning Models for Multi-Class Brain Tumor Classification: Glioma, Meningioma, Pituitary Tumors, and No Tumor MRI Screening.Journal of imaging informatics in medicine · 2026Article
- Applications of transcranial focused ultrasound for primary brain tumors.Neuro-oncology advances · 2026Review
- Brain Tumor Classification in MRI Images Using Combined Transfer Learning and Convolutional Neural Networks.Journal of imaging · 2026Article
- Brain Cancer: Molecular Alterations and Emerging Trends in Neuropharmacology.International journal of molecular sciences · 2026Review
- A Comprehensive Review of Artificial Intelligence for Brain Tumor Analysis: Taxonomy, Robustness, and Open Challenges in Neuro-Oncology.Journal of imaging · 2026Review
- Generative AI for spatial tumor growth on MRI: a proof-of-principle study in pediatric diffuse midline glioma.BMC medicine · 2026Article
- A minimal-net CNN model for an IoT-based brain tumor detection and monitoring system.Scientific reports · 2026Article
- Artificial Intelligence in Oncology: A Comprehensive Cross-Cancer Translational Readiness Analysis Across 18 Malignancies.Cancers · 2026Review
54 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
6 authors.
Funding
Abstract
This review delves into the most recent advancements in applying artificial intelligence (AI) within neuro-oncology, specifically emphasizing work on gliomas, a class of brain tumors that represent a significant global health issue. AI has brought transformative innovations to brain tumor management, utilizing imaging, histopathological, and genomic tools for efficient detection, categorization, outcome prediction, and treatment planning. Assessing its influence across all facets of malignant brain tumor management- diagnosis, prognosis, and therapy- AI models outperform human evaluations in terms of accuracy and specificity. Their ability to discern molecular aspects from imaging may reduce reliance on invasive diagnostics and may accelerate the time to molecular diagnoses. The review covers AI techniques, from classical machine learning to deep learning, highlighting current applications and challenges. Promising directions for future research include multimodal data integration, generative AI, large medical language models, precise tumor delineation and characterization, and addressing racial and gender disparities. Adaptive personalized treatment strategies are also emphasized for optimizing clinical outcomes. Ethical, legal, and social implications are discussed, advocating for transparency and fairness in AI integration for neuro-oncology and providing a holistic understanding of its transformative impact on patient care.
Identifiers
What Socratic 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 Socratic graph.