eng Oriental Scientific Publishing Company Biomedical and Pharmacology Journal 0974-6242 2025-10-27 18 October Spl Edition 68614 article Bhawna Chhabra 1 Malvika Kandpal 5 Prince Raj 2 Arkan 2 Komal Kumari 2 Pushpanjali Kumari 2 Department of Pharmacology, Amity Institute of Pharmacy, Amity University, Noida, Uttar Pradesh, India Department of Pharmaceutics, Uttaranchal Institute of Pharmaceutical Sciences, Uttaranchal University, Dehradun, Uttarakhand, India Department of Pharmaceutical Chemistry, Uttaranchal Institute of Pharmaceutical Sciences, Uttaranchal University, Dehradun, Uttarakhand, India Department of Pharmacology, Faculty of Pharmacy, DIT University, Dehradun, Uttarakhand, India Department of Education, Shri Guru Ram Rai University, Dehradun, Uttarakhand, India The field of computer science known as artificial intelligence (AI) is concerned with simulating human intellect through the use of machines that can replicate the human brain's capacity for problem-solving and decision-making. The scientific study of the brain's structure and cognitive processes is known as neuroscience. AI and neurology have a reciprocal interaction. These two fields benefit from one other's advancements. The notion of neuroscience has brought to a number of novel advancements in the realm of artificial intelligence. Complex deep neural network architectures have been developed because of the biological neural network, which are used to build a variety of applications, including object detection, speech recognition, and text processing. The validation of the current AI-based models is also aided by neuroscience. Artificial systems can now autonomously perform complex tasks because to the development of algorithms that mimic the idea of reinforcement learning, which has been seen in both humans and animals. These algorithms have been applied in various advanced technologies, including surgical robotics, self-driving cars, and intelligent gaming systems. At the same time, AI has proven highly effective in processing complex neurological data by identifying underlying patterns. Large-scale AI simulations offer valuable support to neuroscientists by allowing them to test scientific theories. Through brain-machine interfaces, AI can decode brain signals and convert them into actions, such as controlling robotic limbs to assist individuals with motor impairments. Moreover, AI significantly contributes to the interpretation of neuroimaging data, reducing the burden on radiologists and enhancing diagnostic capabilities. Early identification of brain-related problems is greatly aided by neuroscience, and AI is also being utilized more and more to predict and identify these conditions. This review explores the interconnected roles of AI and neuroscience, highlighting their collaborative potential in diagnosing and predicting neurological diseases, also the opportunities and limitations of these technologies. https://biomedpharmajournal.org/vol18octoberspledition/a-scoping-review-on-the-future-of-neurological-disorder-diagnosis-artificial-intelligence-and-machine-learning/ Algorithms Artificial intelligence Human intelligence Neurosciences Surgical robotics