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International Journal of Advanced Research in Computer and Communication Engineering A monthly Peer-reviewed & Refereed journal
ISSN Online 2278-1021ISSN Print 2319-5940Since 2012
IJARCCE adheres to the suggestive parameters outlined by the University Grants Commission (UGC) for peer-reviewed journals, upholding high standards of research quality, ethical publishing, and academic excellence.
← Back to VOLUME 11, ISSUE 4, APRIL 2022

Alzheimer’s Disease Detection using Machine Learning Techniques

Sumedh Bagaitkar, Atharva Bedade, Tejaswini Bhangare, Abhishek Jagtap

DOI: 10.17148/IJARCCE.2022.11486

Abstract: Alzheimer's disease (AD) is a progressive, irreversible brain illness that affects a person's thinking and causes the brain to shrink, eventually leading to death. It's required for the treatment of early stages of Alzheimer's disease in order to prevent further damage .Machine learning algorithms using various optimization and probabilistic methodologies can be used to make this diagnosis. Because no single non-amyloid protein has been proved to consistently diagnose Alzheimer's disease, using machine learning (ML) techniques to determine optimal combinations of non-amyloid proteins is a potential approach. As a result, our strategy is mostly dependent on machine learning in order to separate persons with normal brain ageing from those who are likely to develop Alzheimer's disease.

How to Cite:

[1] Sumedh Bagaitkar, Atharva Bedade, Tejaswini Bhangare, Abhishek Jagtap, “Alzheimer’s Disease Detection using Machine Learning Techniques,” International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE), DOI: 10.17148/IJARCCE.2022.11486