Artificial intelligence in neurology: opportunities, challenges, and policy implications.
Sebastian VoigtlaenderJohannes PawelczykMario GeigerEugene J VaiosPhilipp KarschniaMerit CudkowiczJorg DietrichIra R J Hebold HaraldsenValery FeiginMayowa OwolabiTara L WhitePaweł ŚwiebodaNita FarahanyVivek NatarajanSebastian F WinterPublished in: Journal of neurology (2024)
Neurological conditions are the leading cause of disability and mortality combined, demanding innovative, scalable, and sustainable solutions. Brain health has become a global priority with adoption of the World Health Organization's Intersectoral Global Action Plan in 2022. Simultaneously, rapid advancements in artificial intelligence (AI) are revolutionizing neurological research and practice. This scoping review of 66 original articles explores the value of AI in neurology and brain health, systematizing the landscape for emergent clinical opportunities and future trends across the care trajectory: prevention, risk stratification, early detection, diagnosis, management, and rehabilitation. AI's potential to advance personalized precision neurology and global brain health directives hinges on resolving core challenges across four pillars-models, data, feasibility/equity, and regulation/innovation-through concerted pursuit of targeted recommendations. Paramount actions include swift, ethical, equity-focused integration of novel technologies into clinical workflows, mitigating data-related issues, counteracting digital inequity gaps, and establishing robust governance frameworks balancing safety and innovation.
Keyphrases
- artificial intelligence
- big data
- healthcare
- public health
- machine learning
- deep learning
- mental health
- resting state
- white matter
- electronic health record
- cerebral ischemia
- health information
- global health
- multiple sclerosis
- functional connectivity
- primary care
- human health
- quality improvement
- cardiovascular events
- type diabetes
- blood brain barrier
- single cell
- drug delivery
- chronic pain
- subarachnoid hemorrhage
- coronary artery disease
- clinical practice
- risk factors
- quantum dots
- data analysis
- advance care planning