ReviewWorld neurosurgery: X2024
Recent Outcomes and Challenges of Artificial Intelligence, Machine Learning, and Deep Learning in Neurosurgery.
Review in World neurosurgery: X, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 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
21 citing papers in PubMed, 5 syntheses or guidelines pooled it.
- Machine learning-based models for preoperative prediction of pituitary adenoma consistency: a systematic review and meta-analysis.Acta neurochirurgica · 2026Pooled it
- Comparisons of artificial intelligence automated segmentation techniques to manual segmentation techniques of the maxilla and maxillary sinus for CT or cone-beam CT scans-a systematic review.Dento maxillo facial radiology · 2025Pooled it
- Artificial intelligence algorithms for differentiating pseudoprogression from true progression in high-grade gliomas: A systematic review and meta-analysis.Neurosurgical review · 2025Pooled it
- Deep learning in neurosurgery: a systematic literature review with a structured analysis of applications across subspecialties.Frontiers in neurology · 2025Pooled it
- Large language models in neurosurgery: a systematic review and meta-analysis.Acta neurochirurgica · 2024Pooled it
- ChatNSG: An Overview of Contemporary and Emerging Artificial Intelligence Models for the Neurosurgeon.Journal of neurological surgery. Part B, Skull base · 2026Article
- A narrative review on artificial intelligence in neurosurgery: ethical challenges and implementation considerations.Annals of medicine and surgery (2012) · 2025Review
- Highly Cited Artificial Intelligence Research Studies Published in Neurosurgical Journals: A Bibliometric Analysis.Cureus · 2025Review
- Diagnostic, Therapeutic, and Prognostic Applications of Artificial Intelligence (AI) in the Clinical Management of Brain Metastases (BMs).Brain sciences · 2025Review
- Artificial Intelligence for Patient Safety and Surgical Education in Neurosurgery.JMA journal · 2025Review
- Applications of deep learning in intracranial aneurysm imaging: A scoping review of detection, risk prediction, and emerging prognostic models.Current journal of neurology · 2025Review
- Knowledge, interest and perspectives on Artificial Intelligence in Neurosurgery. A global survey.Brain & spine · 2025Article
- Artificial intelligence, extended reality, and emerging AI-XR integrations in medical education.Frontiers in digital health · 2025Review
- Machine Learning-Based Prediction of Clinical Outcomes in Microsurgical Clipping Treatments of Cerebral Aneurysms.Diagnostics (Basel, Switzerland) · 2024Article
- Artificial intelligence enhancements in the neurosurgical treatment of tuberous sclerosis.Neurosurgical review · 2024Article
- Harnessing artificial intelligence to improve surgical precision in Chiari malformation.Neurosurgical review · 2024Article
- Artificial Intelligence and Deep Learning in Revolutionizing Brain Tumor Diagnosis and Treatment: A Narrative Review.Cureus · 2024Review
- 7 T and beyond: toward a synergy between fMRI-based presurgical mapping at ultrahigh magnetic fields, AI, and robotic neurosurgery.European radiology experimental · 2024Review
- The Future of Artificial Intelligence in Surgery.Cureus · 2024Review
- The influence of artificial intelligence on neurological surgery and patient outcome.Surgical neurology international · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
14 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Neurosurgeons receive extensive technical training, which equips them with the knowledge and skills to specialise in various fields and manage the massive amounts of information and decision-making required throughout the various stages of neurosurgery, including preoperative, intraoperative, and postoperative care and recovery. Over the past few years, artificial intelligence (AI) has become more useful in neurosurgery. AI has the potential to improve patient outcomes by augmenting the capabilities of neurosurgeons and ultimately improving diagnostic and prognostic outcomes as well as decision-making during surgical procedures. By incorporating AI into both interventional and non-interventional therapies, neurosurgeons may provide the best care for their patients. AI, machine learning (ML), and deep learning (DL) have made significant progress in the field of neurosurgery. These cutting-edge methods have enhanced patient outcomes, reduced complications, and improved surgical planning.
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.