The Science and Information (SAI) Organization
  • Home
  • About Us
  • Journals
  • Conferences
  • Contact Us

Publication Links

  • IJACSA
  • Author Guidelines
  • Publication Policies
  • Metadata Harvesting (OAI2)
  • Digital Archiving Policy
  • Promote your Publication

IJACSA

  • About the Journal
  • Call for Papers
  • Author Guidelines
  • Fees/ APC
  • Submit your Paper
  • Current Issue
  • Archives
  • Indexing
  • Editors
  • Reviewers
  • Apply as a Reviewer

IJARAI

  • About the Journal
  • Archives
  • Indexing & Archiving

Special Issues

  • Home
  • Archives
  • Proposals
  • Guest Editors

Future of Information and Communication Conference (FICC)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Computing Conference

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Intelligent Systems Conference (IntelliSys)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Future Technologies Conference (FTC)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact
  • Home
  • Call for Papers
  • Guidelines
  • Fees
  • Submit your Paper
  • Current Issue
  • Archives
  • Indexing
  • Editors
  • Reviewers
  • Subscribe

Article Details

Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

A Pre-trained Neural Network to Predict Alzheimer’s Disease at an Early Stage

Author 1: Ragavamsi Davuluri
Author 2: Ragupathy Rengaswamy

Download PDF

Digital Object Identifier (DOI) : 10.14569/IJACSA.2022.0130524

Article Published in International Journal of Advanced Computer Science and Applications(IJACSA), Volume 13 Issue 5, 2022.

  • Abstract and Keywords
  • How to Cite this Article
  • {} BibTeX Source

Abstract: Alzheimer’s disease (AD), which is a neuro associated disease, has become a common for past few years. In this competitive world, individual has to perform lot of multi tasking to prove their efficiency, in this process the neurons in the brain gets affected after a while i.e., “Alzheimer’s Disease”. Existing models to identify the disease at early stage has taken the individuals speech as input then they are converted into textual transcripts. These transcripts are analyzed using neural network approached by integrating them with NLP techniques. These techniques failed in designing the model which can process the long conversation text at faster rate and few models are unable to recognize the replacement of the unknown words during the translation process. The proposed system addresses these issues by converting the speech obtained into image format and then the output “Mel-spectrum” is passed as input to pre-trained VGG-16. This process has greatly reduced the pre-processing step and improved the efficiency of the system with less kernel size architecture. The speech to image translation mechanism has improved accuracy when compared to speech to text translators.

Keywords: Mel-spectrum; VGG-16; ADAM optimizer; softmax; flatten layers; ReLU

Ragavamsi Davuluri and Ragupathy Rengaswamy, “A Pre-trained Neural Network to Predict Alzheimer’s Disease at an Early Stage” International Journal of Advanced Computer Science and Applications(IJACSA), 13(5), 2022. http://dx.doi.org/10.14569/IJACSA.2022.0130524

@article{Davuluri2022,
title = {A Pre-trained Neural Network to Predict Alzheimer’s Disease at an Early Stage},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2022.0130524},
url = {http://dx.doi.org/10.14569/IJACSA.2022.0130524},
year = {2022},
publisher = {The Science and Information Organization},
volume = {13},
number = {5},
author = {Ragavamsi Davuluri and Ragupathy Rengaswamy}
}


IJACSA

Upcoming Conferences

Future of Information and Communication Conference (FICC) 2023

2-3 March 2023

  • Virtual

Computing Conference 2023

22-23 June 2023

  • London, United Kingdom

IntelliSys 2023

7-8 September 2023

  • Amsterdam, The Netherlands

Future Technologies Conference (FTC) 2023

2-3 November 2023

  • San Francisco, United States
The Science and Information (SAI) Organization
BACK TO TOP

Computer Science Journal

  • About the Journal
  • Call for Papers
  • Submit Paper
  • Indexing

Our Conferences

  • Computing Conference
  • Intelligent Systems Conference
  • Future Technologies Conference
  • Communication Conference

Help & Support

  • Contact Us
  • About Us
  • Terms and Conditions
  • Privacy Policy

© The Science and Information (SAI) Organization Limited. Registered in England and Wales. Company Number 8933205. All rights reserved. thesai.org