The Nature and the Limitations of the Technology used for Telemedicine in Neurology

The pandemic fundamentally changed our lives and accelerated the adoption of artificial intelligence in the medical field. Despite the undeniable contribution of artificial intelligence, medical experiments and human knowledge are still necessary. The aim of this study is to compare the use of AI and ML in neurology as an effective method for screening, detection, evaluation, monitoring and development of neurological diseases. This article review was conducted on databases correlating the application of ML and AI techniques to the health law. It also addresses some of the disadvantages of applying medical algorithms to real-world and difficulties from a health law perspective. The study also considers the recommendations of researchers, clinical experts and policy makers for a model strategy to explore technology in the future. Current improvements in AI and ML have significantly improved neurological treatment - but also detection, evaluation and at the same time reduced human intervention in medical practice. Article seeks sustained and organised effort to treat neurological patients faster with the cultural, political, and economic pressures under which medicine functions.