ReviewFederal practitioner : for the health care professionals of the VA, DoD, and PHS2022
Neuroimaging in the Era of Artificial Intelligence: Current Applications.
Review in Federal practitioner : for the health care professionals of the VA, DoD, and PHS, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers, 1 of them a synthesis 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
30 citing papers in PubMed, 1 synthesis or guideline pooled it, 52 citations in OpenAlex.
- Neuroimage analysis using artificial intelligence approaches: a systematic review.Medical & biological engineering & computing · 2024Pooled it
- Artificial Intelligence in Veterinary Neurology: Comparative Insights From Human Medicine and Cross-Species Technology Transfer.Veterinary medicine and science · 2026Review
- Obstacles and Trials in Treating Primary Brain Tumors.International journal of molecular sciences · 2026Review
- Artificial intelligence-based biomarkers for the diagnosis and treatment of neurological conditions: a narrative review.Molecular brain · 2026Review
- A Comprehensive Analysis of Natural Bioactive Molecules for the Treatment and Control of Glioblastoma Multiforme (GBM) Targeting Underlying Molecular Mechanism.Chemistry & biodiversity · 2026Review
- Review
- Neurosurgery 4.0: A Scoping Review of Current Trends and Challenges in Specialized Smart Hospitals.Cureus · 2025Review
- Multidisciplinary, Clinical Assessment of Accelerated Deep-Learning MRI Protocols at 1.5 T and 3 T After Intracranial Tumor Surgery and Their Influence on Residual Tumor Perception.Diagnostics (Basel, Switzerland) · 2025Article
- An update on recent advances in fluorescent materials for fluorescence molecular imaging: a review.RSC advances · 2025Review
- Advancing Neurosurgical Oncology and AI Innovations in Latin American Brain Cancer Care: Insights from a Center of Excellence.NeuroSci · 2025Review
- Review
- Advances of Artificial Intelligence in Neuroimaging.Brain sciences · 2025Article
- Review
- Pathological Mechanisms and Molecular Imaging Advances in Alzheimer's Disease.Clinical interventions in aging · 2025Review
- How to Implement Clinical 7T MRI-Practical Considerations and Experience with Ultra-High-Field MRI.Bioengineering (Basel, Switzerland) · 2024Article
- Multidisciplinary quantitative and qualitative assessment of IDH-mutant gliomas with full diagnostic deep learning image reconstruction.European journal of radiology open · 2024Article
- Radiomic Features as Artificial Intelligence Prognostic Models in Glioblastoma: A Systematic Review and Meta-Analysis.Diagnostics (Basel, Switzerland) · 2024Review
- Leveraging State-of-the-Art AI Algorithms in Personalized Oncology: From Transcriptomics to Treatment.Diagnostics (Basel, Switzerland) · 2024Article
- Tai Chi Practice Buffers Aging Effects in Functional Brain Connectivity.Brain sciences · 2024Article
- Revolutionizing Neurology: The Role of Artificial Intelligence in Advancing Diagnosis and Treatment.Cureus · 2024Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Artificial intelligence (AI) in medicine has shown significant promise, particularly in neuroimaging. AI increases efficiency and reduces errors, making it a valuable resource for physicians. With the increasing amount of data processing and image interpretation required, the ability to use AI to augment and aid the radiologist could improve the quality of patient care. Observations: AI can predict patient wait times, which may allow more efficient patient scheduling. Additionally, AI can save time for repeat magnetic resonance neuroimaging and reduce the time spent during imaging. AI has the ability to read computed tomography, magnetic resonance imaging, and positron emission tomography with reduced or without contrast without significant loss in sensitivity for detecting lesions. Neuroimaging does raise important ethical considerations and is subject to bias. It is vital that users understand the practical and ethical considerations of the technology. Conclusions: The demonstrated applications of AI in neuroimaging are numerous and varied, and it is reasonable to assume that its implementation will increase as the technology matures. AI's use for detecting neurologic conditions holds promise in combatting ever increasing imaging volumes and providing timely diagnoses.
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.