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    Artificial intelligence based Alzheimer’s disease detection using deep feature extraction

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    Author
    Kapadnis, Manav Nitin
    Bhattacharyya, Abhijit
    Subasi, Abdulhamit cc
    Subject
    Alzheimer’s Disease (AD) Diagnosis
    Artificial Intelligence (AI)
    Deep Feature Extraction
    Machine Learning
    Date
    2023-01-20
    
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    Abstract
    Alzheimer’s disease (AD) is an acute brain disease that affects neural functions and destroys the memories and abilities of human beings. AD causes severe chronic, progressive, and irreversible cognitive declination and brain damage. It is one of the most common forms of dementia that affects the elderly. Early identification of AD is critical for developing new treatment options. Artificial intelligence (AI) is an excellent tool for detecting AD since these methods are used in clinical settings as a computer-aided diagnosis (CAD) system and play an important role in detecting alterations in brain images for AD detection. This chapter discusses the recent methods and developments in medical image analysis and image processing for AD detection using AI. The primary objective of this chapter is the development of easy-to-implement methods that promote early AD detection based on deep feature extraction methods. We developed a deep feature extraction methodology with machine learning approaches to achieve a good performance in AD detection. Furthermore, some of the techniques that were used by previous researchers are reviewed. A discussion on the existing state-of-the-art methods, a review of emerging trends, and future research problems will round up the chapter
    Department
    Computer Science
    Publisher
    Academic Press
    Book title
    Applications of Artificial Intelligence in Medical Imaging.
    DOI
    https://doi.org/10.1016/B978-0-443-18450-5.00007-4
    ae974a485f413a2113503eed53cd6c53
    https://doi.org/10.1016/B978-0-443-18450-5.00007-4
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