Paper Title
Detection Of Alzheimer's Disease Using Deep Learning
Article Identifiers
: Keywords
Alzheimer's disease, Ailment, Convolutional Neural Networks, Magnetic Resonance Imaging.
Abstract
Millions of individuals throughout the world are afflicted with the progressive neurological ailment known as Alzheimer's disease. For Alzheimer's disease to be effectively treated and managed, early diagnosis is essential. . The ability of convolutional neural networks (CNNs) to identify Alzheimer's disease from medical pictures has shown considerable promise. CNN is a deep learning method that is frequently employed for pattern identification and picture analysis. In this approach, a CNN-based method for exploiting Magnetic Resonance Imaging (MRI) data to identify Alzheimer's disease is used. The dataset of MRI scans from people with Alzheimer's disease and healthy people are collected. To improve the picture quality and lower noise, the MRI scans undergo pre-processing. A CNN model is trained using the pre-processed pictures, and it is then tuned using fine-tuning methods. This CNN-based method for Alzheimer's disease detection may help doctors identify the condition early and begin therapy. The adoption of CNN models for Alzheimer's disease detection can increase diagnostic precision and lower visual interpretation variability. The method can assist in decreasing the expense and time involved in MRI scan interpretation, making it a more effective and economical method for detecting Alzheimer's disease.
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How To Cite (APA)
Adithya Dinesh, Abhithesh Ramachandran, Dr.Rejeesh Rayaroth, Aswan Krishnan, & Hemanth Suresh (May-2023). Detection Of Alzheimer's Disease Using Deep Learning. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 8(5), f187-f190. https://ijnrd.org/papers/IJNRD2305538.pdf
Issue
Volume 8 Issue 5, May-2023
Pages : f187-f190
Other Publication Details
Paper Reg. ID: IJNRD_196153
Published Paper Id: IJNRD2305538
Downloads: 000121984
Research Area: Engineering
Author Type: Indian Author
Country: Hosabettu, Karnataka, India
Published Paper PDF: https://ijnrd.org/papers/IJNRD2305538.pdf
Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2305538
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