Taiwanese researchers conducted an exhaustive analysis of the literature on artificial intelligence (AI) tools in the context of predictive factors at certain stages of myasthenia gravis:
- a PRISMA-type approach was used to select 11 studies,
- which focused on prediction tools based on machine learning algorithms,
- with particular attention paid to admission to intensive care, length of hospitalisation, occurrence of myasthenic crises, and use of ventilation, among other factors.
The authors highlight the wide variety of tools used and objectives targeted, resulting in expectations that have not yet been met in this field despite its real potential.
