DNA Sequence Analysis for Brain Disorder Using Deep Learning and Secure Storage

作     者：Ala Saleh Alluhaidan 

作者机构：Departmemt of Information SystemsCollege of Computer and Information SciencePrincess Nourah Bint Abdulrahman UniversityRiyadh 11671Saudi Arabia 

出 版 物：《Computers, Materials & Continua》 (计算机、材料和连续体（英文）)

年 卷 期：2022年第71卷第6期

页      面：5949-5962页

核心收录：

学科分类：0831[工学-生物医学工程（可授工学、理学、医学学位）] 0710[理学-生物学] 1002[医学-临床医学] 1001[医学-基础医学(可授医学、理学学位)] 0805[工学-材料科学与工程（可授工学、理学学位）] 0714[理学-统计学（可授理学、经济学学位）] 0701[理学-数学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 0702[理学-物理学] 10[医学] 

基　　金：This research was funded by Princess Nourah bint Abdulrahman University Researchers Supporting Project number(PNURSP2022R234) Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia 

主　　题：DBN Zig zag deep learning MAPE RMSE DNA genomics 

摘      要：Analysis of brain disorder in the neuroimaging of Magnetic Resonance Imaging(MRI),Positron Emission Tomography(PET),and Computed Tomography(CT)needs to understand the functionalities of the brain and it has been performed using *** learning algorithms have also been applied in genomics data *** brain disorder diseases of Alzheimer,Schizophrenia,and Parkinson are analyzed in this *** main issue in the traditional algorithm is the improper detection of disorders in the neuroimaging *** paper presents a deep learning algorithm for the classification of brain disorder using Deep Belief Network(DBN)and securely storing the image using a Deoxyribonucleic Acid(DNA)Sequence-based Joint Photographic Experts Group(JPEG)Zig Zag Encryption Algorithm(DBNJZZ).In this work,DBNJZZ implements an efficient and effective prediction model for disorders using the open-access datasets of Alzheimer’s Disease Neuroimaging Initiative(Adni),the Center for Biomedical Research Excellence(Cobre),the Open Access Series of Imaging Studies(Oasis),the Function Biomedical Informatics Research Network(Fbirn),a Parkinson’s dataset of 55 patients and 23 subjects with Parkinson’s syndromes(Ntua),and the Parkinson’s Progression Markers Initiative(Ppmi).This algorithm is implemented and tested using performance metric measures of accuracy,Root Mean Square Error(RMSE),Mean Absolute Error(MAE),and Mean Absolute Percentage Error(MAPE).DBNJZZ gives better performance with an accuracy of 99.21%and also surpasses previous methods on other measures.