Certain Studies on Alzheimer's disease: A Comprehensive Review
DOI:
https://doi.org/10.47392/IRJAEH.2024.0211Keywords:
ConvNet, Deep Learning, Alzheimer's Disease (AD), Traumatic Brain Injury (TBI)Abstract
The brain serves as the central control centre for our body, and as time progresses, an increasing number of new brain diseases are being identified. A brain disease is any medical problem or disorder that interferes with the brain's normal functioning. This review briefs about various types of deep learning models for neurological disorders, in addition to neurodegenerative conditions like Parkinson's and Alzheimer's. In addition to various dataset identifiers commonly used as the primary source of brain disease data in the reviewed studies, forty other methodologies are examined. AUC, sensitivity, specificity, accuracy, and other performance evaluation parameters have also been addressed and recorded. The key findings from the reviewed articles are briefly summarized, and several major issues regarding machine learning and deep learning-based diagnostic approaches for brain diseases are discussed.
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