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Artificial intelligence and Machine learning-based approaches for Neurodegenerative Diseases Diagnosis
ISSN: 2583 - 7117
Publisher: author
Artificial intelligence and Machine learning-based approaches for Neurodegenerative Diseases Diagnosis
Indexed in
Technology and Engineering
ARTICLE-FACTOR
1.3
Article Basics Score: 3
Article Transparency Score: 2
Article Operation Score: 2
Article Articles Score: 2
Article Accessibility Score: 2
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International Category Code (ICC):
ICC-1802
Publisher: Ag Publishing House
International Journal Address (IAA):
IAA.ZONE/2583405987117
eISSN
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2583 - 7117
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Abstract
This review paper delves into the transformative impact of machine learning on the diagnosis of neurodegenerative diseases, such as Alzheimer's, Parkinson's, and ALS. The importance of high-quality medical data, diverse data sources, and specific machine learning algorithms, including Support Vector Machines, Convolutional Neural Networks, and Long Short-Term Memory networks, is emphasized. Case studies showcase the practical applications of machine learning, highlighting the methodologies, findings, and limitations of various projects. Machine learning's significance in advancing neurodegenerative disease diagnosis lies in its ability to enable early detection, enhance diagnostic accuracy, and facilitate personalized treatment strategies. The future of machine learning in this field is marked by the integration of diverse data modalities, interpretable models, ethical considerations, the recognition of disease heterogeneity, and the ...
