Revolutionizing Brain Analysis: AI-Powered Insights for Neuroscience

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.

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Publication Details

Journal
INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT
Published
2024-12-18
DOI
https://doi.org/10.55041/ijsrem39852
Primary Topic
Brain Tumor Detection and Classification
Type
article
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article

Revolutionizing Brain Analysis: AI-Powered Insights for Neuroscience

V. Sivanagaraju, P. Tulasi Ram, T. Trinath Reddy
INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT
Brain Tumor Detection and Classification
article

Revolutionizing Brain Analysis: AI-Powered Insights for Neuroscience

V. Sivanagaraju, P. Tulasi Ram, T. Trinath Reddy
article en

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.

INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENTVol. 08(12)
Institut Icare (CH)
Openalex Percentile: Top 73%
Brain Tumor Detection and Classification
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Revolutionizing Brain Analysis: AI-Powered Insights for Neuroscience — V. Sivanagaraju, P. Tulasi Ram, et al. · INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT (2024) | TGRS Research Map | TGRS