Alzheimer detection using Machine Learning: A review

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Khosheh BastBaghsangani Mostafa; Mia Soheila

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Seminar Paper

Paper Information

Seminar: CONFERENCE ON RECENT RESEARCH IN SCIENCE AND TECHNOLOGY
Year:2023 | Issue:24

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Title

Alzheimer detection using Machine Learning: A review

Author(s)

Khosheh BastBaghsangani Mostafa | Mia Soheila

Keywords

Alzheimer Disease

Machine Learning

Detection

Diagnosis

Early detection

Abstract

Alzheimer's disease (AD) is a brain disorder that slowly destroys memory and the ability to think, and symptoms eventually grow severe enough to interfere with daily tasks. Alzheimer's is a progressive disease, where dementia symptoms grADually worsen over a number of years. Thus it is very helpful to diagnose this disease in its early stage. There are several methods and tools to determine Alzheimer’, s. However, diagnosing AD base on Machine Learning and brain imaging such as CT, MRI, PET and etc is the most reliable way to detect this disease in the early stage. Machine Learning (ML) has become a major part of medical imaging research. It can completely change the working layout of the healthcare facilities while detecting and predicting diseases with a superior level of care and satisfaction. This paper aims to review the impact of Machine Learning systems for detecting early-stage Alzheimer’, s Disease using imaging techniques.

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APA: Copy

Khosheh BastBaghsangani, Mostafa, & Mia, Soheila. (2023). Alzheimer detection using Machine Learning: A review. INTERNATIONAL CONFERENCE ON RECENT RESEARCH IN SCIENCE AND TECHNOLOGY. SID. https://sid.ir/paper/1040206/en

Vancouver: Copy

Khosheh BastBaghsangani Mostafa, Mia Soheila. Alzheimer detection using Machine Learning: A review. 2023. Available from: https://sid.ir/paper/1040206/en

IEEE: Copy

Mostafa Khosheh BastBaghsangani, and Soheila Mia, “Alzheimer detection using Machine Learning: A review,” presented at the INTERNATIONAL CONFERENCE ON RECENT RESEARCH IN SCIENCE AND TECHNOLOGY. 2023, [Online]. Available: https://sid.ir/paper/1040206/en

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