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Alzheimer's disease is a slowly progressing neurological condition that predominantly impacts cognitive skills, it is essential to diagnose the disease early and accurately in order to provide appropriate treatment and patient care. In the realm of medical image analysis, recent developments in deep learning techniques, in particular Convolutional Neural Networks (CNNs), have demonstrated a great deal of promise. This research outlines an innovative strategy for the early diagnosis of Alzheimer's disease that makes use of CNNs. This research makes use of a database of brain magnetic resonance imaging (MRI) scans. This database contains images from people who have been diagnosed with Alzheimer's disease as well as healthy individuals. This research demonstrates that CNNs have the potential to be an effective diagnostic tool for Alzheimer's disease when used in conjunction with MRI images. The application of techniques from deep learning in medical imaging holds the potential to improve the accuracy and effectiveness of Alzheimer's disease diagnosis, which would ultimately be to the advantage of persons who are at risk and would make it easier to begin early intervention and treatment.
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Poonam Shourie
Vatsala Anand
Deepak Upadhyay
Chitkara University
Himachal Pradesh University
Graphic Era University
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Shourie et al. (Fri,) studied this question.
www.synapsesocial.com/papers/68e76b0eb6db6435876e11fe — DOI: https://doi.org/10.1109/inocon60754.2024.10511648
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