Background/Objectives: The purpose of this study was to classify Alzheimer’s disease (AD) patients from Normal Control (NC) patients using Magnetic Resonance Imaging (MRI). Methods/Statistical analysis: The performance evolution is carried out for 346 MR images from Alzheimer's Neuroimaging Initiative (ADNI) dataset. The classifier Deep Belief Network (DBN) is used for the function of classification. The network is trained using a sample training set, and the weights produced are then used to check the system's recognition capability. Findings: As a result, this paper presented a novel method of automated classification system for AD determination. The suggested method offers good performance of the experiments carried out show that the use of Gray Level Co-occurrence Matrix (GLCM) features and DBN classifier provides 98.26% accuracy with the two specific classes were tested. Improvements/Applications: AD is a neurological condition affecting the brain and causing dementia that may affect the mind and memory. The disease indirectly impacts more than 15 million relatives, companions and guardians. The results of the present research are expected to help the specialist in decision making process.
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Abstract This research deals with the definition of the concept of nodal purposes, And what is related to it, from its aim and importance, And for the purposes of the importance of Streptococcus In trying to understand the nodal truths For different minds, Especially with those who object to the introduction of belief in purposes studies, This research has two requirements: The first requirement: the concept and the aim of contractual purposes,It consists of two branches, The first is in the concept of nodal purposes, And it dealt with the definitions in terms of language and terminology And what we see is proportional to what aim |
حسن السيد عز الدين بحر العلوم العقد الاجتماعي والسلطة الشعبية عند الإمام علي (عليه السلام )
Digital tampering identification, which detects picture modification, is a significant area of image analysis studies. This area has grown with time with exceptional precision employing machine learning and deep learning-based strategies during the last five years. Synthesis and reinforcement-based learning techniques must now evolve to keep with the research. However, before doing any experimentation, a scientist must first comprehend the current state of the art in that domain. Diverse paths, associated outcomes, and analysis lay the groundwork for successful experimentation and superior results. Before starting with experiments, universal image forensics approaches must be thoroughly researched. As a result, this review of variou
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AbstractBackground:Reduced glomeular filtration rate isassociated with increasedmorbidity in patientswith coronary arterydisease.Objectives :To analyze the declining eGFR andmortality risks in a patients with Chronic KidneyDisease and have had Coronary Artery Diseaseincluding risk factors .Patientsand Methods:The study included (160)patientsbetween the ages of 16 and 87years.Glomerular filtration rate was estimated (eGFR)using the Modification of Diet in Renal Diseaseequationand was categorized in the ranges<60 mL· min−1 per 1.73 m2and≥ 60 ml/min/1.73 m2.Baseline risk factors were analyzed by category ofeGFR,.The studied patients in emergencydepartment, were investigatedusing Coxproportional hazard models adjusting for traditiona
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