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 

作者机构：Computer Sciences DepartmentCollege of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadhP.O.Box 8442811671KSA School of Computer Scence and EngineeringVellore Institute of TechnologyChennai600127India Department of Computer ScienceCHRIST(Deemed to be University)Bangalore560029India 

出 版 物：《Computer Systems Science & Engineering》 (计算机系统科学与工程（英文）)

年 卷 期：2023年第45卷第6期

页      面：2447-2460页

核心收录：

学科分类：1002[医学-临床医学] 10[医学] 

主　　题：Deep belief networks zig zag deep learning mean absolute percentage error mean absolute error root mean square error DNA genomics 

摘      要：In order to research brain problems using MRI,PET,and CT neuroimaging,a correct understanding of brain function is *** has been considered in earlier times with the support of traditional *** learning process has also been widely considered in these genomics data processing *** 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 ***,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)*** 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 *** DBNJZZ gives better performance than previously available methods.