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

作　　者：Ahmed Zohair Ibrahim P.Prakash V.Sakthivel P.Prabu 

机构地区：[1]Computer Sciences Department,College of Computer and Information Sciences,Princess Nourah Bint Abdulrahman University,Riyadh,P.O.Box 84428,11671,KSA [2]School of Computer Scence and Engineering,Vellore Institute of Technology,Chennai,600127,India [3]Department of Computer Science,CHRIST(Deemed to be University),Bangalore,560029,India

出　　处：《Computer Systems Science & Engineering》2023年第6期2447-2460,共14页计算机系统科学与工程（英文）

摘　　要：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.

关 键 词：Deep belief networks zig zag deep learning mean absolute percentage error mean absolute error root mean square error DNA GENOMICS 

分 类 号：R74[医药卫生—神经病学与精神病学] TP181[医药卫生—临床医学]