Year: 2024
Type: article
Abstract: The integration of artificial intelligence (AI) into neuroscience has revolutionized brain analysis, offering unprecedented insights into neural structures, functions, and disorders. This study explores the application of AI techniques such as machine learning and deep learning in brain imaging, cognitive analysis, and neurological diagnostics. By leveraging advanced algorithms, we analyze complex datasets from modalities like MRI, fMRI, and EEG, enabling the identification of intricate patterns and anomalies in brain activity. The findings demonstrate the potential of AI in improving diagnostic accuracy, predicting neurodegenerative conditions, and enhancing our understanding of the human brain. Despite its transformative capabilities, challenges such as data privacy, interpretability, and ethical considerations persist. This research underscores the critical role of AI in shaping the future of neuroscience and paves the way for its wider adoption in clinical and research settings. Keywords - fMRI (Functional Magnetic Resonance), Imaging, EEG (Electroencephalogram), Neurological Diagnostics, Neurodegenerative Conditions, Pattern Recognition.
DOI: 10.55041/ijsrem39852
Language: English
Subfield: Health Informatics
Field: Medicine
Domain: Health Sciences
Open Access status: bronze
OpenAlex ID: W4405526365