BACKGROUND AND PURPOSE: The integration of artificial intelligence (AI) in healthcare has the potential to revolutionize patient care and clinical decision-making. This study aimed to explore the reliability of large language models in neurology by c...
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 Gl...
INTRODUCTION: The use of artificial intelligence technology is progressively expanding and advancing in the health and biomedical literature. Since its launch, ChatGPT has rapidly gained popularity and become one of the fastest-growing artificial int...
Annals of clinical and translational neurology
38581138
OBJECTIVE: Artificial intelligence (AI)-based decision support systems (DSS) are utilized in medicine but underlying decision-making processes are usually unknown. Explainable AI (xAI) techniques provide insight into DSS, but little is known on how t...
Artificial intelligence (AI) is currently being used as a routine tool for day-to-day activity. Medicine is not an exception to the growing usage of AI in various scientific fields. Vascular and interventional neurology deal with diseases that requir...
Large language models (LLMs) are advanced artificial intelligence (AI) systems that excel in recognizing and generating human-like language, possibly serving as valuable tools for neurology-related information tasks. Although LLMs have shown remarkab...
As teleheath becomes integrated into the practice of medicine, it is important to understand the benefits, limitations, and variety of applications. Telestroke was an early example of teleneurology that arose from a need for urgent access to neurolog...
Journal of neuro-ophthalmology : the official journal of the North American Neuro-Ophthalmology Society
38965655
BACKGROUND: Neuro-ophthalmology frequently requires a complex and multi-faceted clinical assessment supported by sophisticated imaging techniques in order to assess disease status. The current approach to diagnosis requires substantial expertise and ...
Machine learning (ML) methods are becoming more prevalent in the neurology literature as alternatives to traditional statistical methods to address challenges in the analysis of modern data sets. Despite the increase in the popularity of ML methods i...