Integrated Approach of Brain Disorder Analysis by Using Deep Learning Based on DNA Sequence

Title

Integrated Approach of Brain Disorder Analysis by Using Deep Learning Based on DNA Sequence

Creator

Ibrahim A.Z.; Prakash P.; Sakthivel V.; Prabu P.

Description

In order to research brain problems using MRI, PET, and CT neuroimaging, a correct understanding of brain function is required. This has been considered in earlier times with the support of traditional algorithms. Deep learning process has also been widely considered in these genomics data processing system. In this research, brain disorder illness incliding Alzheimer's disease, Schizophrenia and Parkinson's diseaseis is analyzed owing to misdetection of disorders in neuroimaging data examined by means fo traditional methods. Moeover, deep learning approach is incorporated here for classification purpose of brain disorder with the aid of Deep Belief Networks (DBN). Images are stored in a secured manner by using DNA sequence based on JPEG Zig Zag Encryption algorithm (DBNJZZ) approach. The suggested approach is executed and tested by using the performance metric measure such as accuracy, root mean square error, Mean absolute error and mean absolute percentage error. Proposed DBNJZZ gives better performance than previously available methods. 2023 Authors. All rights reserved.

Source

Computer Systems Science and Engineering, Vol-45, No. 3, pp. 2447-2460.

Date

2023-01-01

Publisher

Tech Science Press

Subject

Deep belief networks; deep learning; DNA; genomics; mean absolute; mean absolute error; percentage error; root mean square error; zig zag

Coverage

Ibrahim A.Z., Computer Sciences Department, College of Computer and Information Sciences, Princess Nourah Bint Abdulrahman University, P.O. Box 84428, Riyadh, 11671, Saudi Arabia; Prakash P., School of Computer Scence and Engineering, Vellore Institute of Technology, Chennai, 600127, India; Sakthivel V., School of Computer Scence and Engineering, Vellore Institute of Technology, Chennai, 600127, India; Prabu P., Department of Computer Science, CHRIST (Deemed to be University), Bangalore, 560029, India

Rights

All Open Access; Hybrid Gold Open Access

Relation

ISSN: 2676192; CODEN: CSSEE

Format

Online

Language

English

Type

Article

Identifier

https://doi.org/10.32604/csse.2023.030134

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