The Possibilities of Artificial Intelligence in the Detection and Control of Neurological Disorders

In 1956, the American computer scientist John McCartney was the first to introduce the term and principles of artificial intelligence (AI). The term ‘artificial intelligence’ is used to describe ‘machines’ capable of demonstrating cognitive functions that humans associate with the human mind, such as ‘learning’ and ‘problem solving’. AI has become a revolutionary tool in the field of healthcare, especially in the field of early detection and accurate diagnosis of neurological disorders. AI's mastery of medical imaging analysis has significantly advanced this field, making it possible to identify neurological abnormalities in detail and accurately. By carefully analyzing MRI, CT, and X-ray images, AI-driven algorithms succeed in detecting subtle patterns indicative of various neurological disorders such as Alzheimer's disease, Parkinson's disease, multiple sclerosis, and brain tumors. These technologies not only increase the accuracy of diagnosis, but also allow for early intervention and improved patient outcomes. Moreover, AI uses extensive datasets, including medical histories, genetic information, and biosensor data, to predict and assess human susceptibility to neurological disorders. Ethical considerations highlight the importance of implementing AI in the detection of neurological disorders, emphasizing the need for transparent algorithms, strict data protection protocols, and unbiased AI systems to ensure patient confidentiality and trust in healthcare