ReviewAnnals of neurology2025
AI in Neurology: Everything, Everywhere, All at Once Part 3: Surveillance, Synthesis, Simulation, and Systems.
Review in Annals of neurology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 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
5 citing papers in PubMed.
- Artificial Intelligence in Veterinary Neurology: Comparative Insights From Human Medicine and Cross-Species Technology Transfer.Veterinary medicine and science · 2026Review
- Identifying and Predicting Cognitive Decline Using Multi-Modal Sensor Data and Machine Learning Approach.Research square · 2025Article
- AI-Driven Advances in Parkinson's Disease Neurosurgery: Enhancing Patient Selection, Trial Efficiency, and Therapeutic Outcomes.Brain sciences · 2025Review
- Precision neurodiversity: personalized brain network architecture as a window into cognitive variability.Frontiers in human neuroscience · 2025Review
- Digital twins in dementia: Early evidence and future directions for precision psychiatry.Industrial psychiatry journalArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
Abstract
This final part 3 review builds on the practical applications discussed in part 2 and explores how artificial intelligence (AI) is transforming data management, neurological education, and neurological care across large healthcare networks and datasets. The review also highlights AI's role in real-world and synthetic data, digital twins, and innovative clinical trial designs, such as in silico and adaptive trials. The review emphasizes AI's ability to drive continuous improvements in care and discovery through comparative effectiveness research and learning health systems. The global healthcare implications discussed here tie back to earlier discussions on human-AI collaboration and precision care, underscoring the neurological sciences' responsibility to adopt AI advances judiciously, while managing their ethical, economic, and environmental impacts. ANN NEUROL 2025;98:651-667.
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.