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Artificial intelligence-based tools have the potential to transform health care, enabling faster and more accurate diagnosis, personalized treatment plans, new therapeutic approaches and effective disease monitoring. Artificial intelligence shows particular promise for the management of rare neurological disorders by augmenting knowledge and facilitating the sharing of expertise among physicians.
Data-driven approaches hold considerable promise for medical breakthroughs in the precision and cost-effectiveness of the prevention, diagnosis and treatment of neurodegenerative diseases. The scientists and health care professionals who will be responsible for providing the evidence to support these approaches must also consider the ethical challenges involved in the care of people with intellectual impairments.
Artificial intelligence has emerged as a powerful tool for predicting protein structure. This technology is now being applied to improve our understanding of protein aggregation in neurodegenerative and other neurological disorders, and could potentially improve disease management by enabling precision medicine.
Deep brain stimulation (DBS) is a well-established approach for treating movement disorders such as Parkinson disease, dystonia and essential tremor. However, the outcomes are variable, and researchers are now exploring artificial intelligence-based strategies to help improve DBS procedures.
The overarching theme of the ninth Congress of the European Academy of Neurology (1–4 July 2023) is ‘neurology beyond big data’. The Congress provides an opportunity for neurologists, neuroscientists and other experts to discuss how the power of neurological data might be harnessed to advance discovery and improve patient outcomes and brain health.
Digital technologies for data collection and remote monitoring can offer several indubitable advantages in neurological disorders. However, an equitable future for the use of digital technology in neurology will be possible only with global, collaborative and multidisciplinary planning that should be promptly prepared and implemented.
A growing understanding of the neurobiology of psychosis offers hope for an improvement in the standard of care; this includes the development of individualized, precision therapeutics. However, the path to precision psychiatry is long, and progress would be accelerated by greater collaboration with the fields of neurology and neuroscience.
Prediction tools offer great promise for clinicians in the prevention and treatment of psychosis, but none has been routinely implemented. Greater methodological rigour in the development and evaluation of these tools, along with consideration of a range of performance criteria, is necessary to maximize their potential for improving clinical decision making.
