Detection Of Alzheimer's Disease Using Deep Learning

Registration ID: IJNRD_196153

Published ID: IJNRD2305538

DOI: Click Here to Get

Adithya Dinesh , Abhithesh Ramachandran , Dr.Rejeesh Rayaroth , Aswan Krishnan , Hemanth Suresh

Alzheimer's disease, Ailment, Convolutional Neural Networks, Magnetic Resonance Imaging.

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.

Published Paper   E-Certificate

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

Volume 8 Issue 5, May-2023

Pages : f187-f190

Paper Reg. ID: IJNRD_196153

Published Paper Id: IJNRD2305538

Downloads: 000121977

Research Area: Engineering

Country: Hosabettu, Karnataka, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2305538.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2305538

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Publisher: IJNRD (IJ Publication) Janvi Wave | IJNRD.ORG | IJNRD.COM | IJPUB.ORG

This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition

Call For Paper - Volume 10 | Issue 10 | October 2025

IJNRD is a Scholarly Open Access, Peer-reviewed, and Refereed Journal with a High Impact Factor of 8.76 (calculated by Google Scholar & Semantic Scholar | AI-Powered Research Tool). It is a Multidisciplinary, Monthly, Low-Cost Journal that follows UGC CARE 2025 Peer-Reviewed Journal Policy norms, Scopus journal standards, and Transparent Peer Review practices to ensure quality and credibility. IJNRD provides indexing in all major databases & metadata repositories, a citation generator, and Digital Object Identifier (DOI) for every published article with full open-access visibility.

The INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (IJNRD) aims to advance applied, theoretical, and experimental research across diverse fields. Its goal is to promote global scientific information exchange among researchers, developers, engineers, academicians, and practitioners. IJNRD serves as a platform where educators and professionals can share research evidence, models of best practice, and innovative ideas, contributing to academic growth and industry relevance.

Indexing Coverage includes Google Scholar, SSRN, ResearcherID-Publons, Semantic Scholar (AI-Powered Research Tool), Microsoft Academic, Academia.edu, arXiv.org, ResearchGate, CiteSeerX, ResearcherID (Thomson Reuters), Mendeley, DocStoc, ISSUU, Scribd, and many more recognized academic repositories.

How to submit the paper?

By Our website

Click Here to Submit Paper Online

By Mail

Send your paper to editor@ijnrd.org

Important Dates for Current issue

Paper Submission Open For: October 2025

Current Issue: Volume 10 | Issue 10 | October 2025

Impact Factor: 8.76

Last Date for Paper Submission: Till 31-Oct-2025

Notification of Review Result: Within 1-2 Days after Submitting paper.

Publication of Paper: Within 01-02 Days after Submititng documents.

Frequency: Monthly (12 issue Annually).

Journal Type: IJNRD is an International Peer-reviewed, Refereed, and Open Access Journal with Transparent Peer Review as per the new UGC CARE 2025 guidelines, offering low-cost multidisciplinary publication with Crossref DOI and global indexing.

Subject Category: Research Area

Call for Paper: More Details