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.
طريقة سهلة وبسيطة ودقيقة لتقدير السبروفلوكساسين في وجود السيفاليكسين او العكس بالعكس في خليط منهما. طبقت الطريقة المقترحة بطريقة الاضافة القياسية لنقطة بنجاح في تقدير السبروفلوكساسين بوجود السيفاليكسين كمتداخل عند الاطوال الموجية 240-272.3 نانوميتر وبتراكيز مختلفة من السبروفلوكساسين 4-18 مايكروغرام . مل-1 وكذلك تقدير السيفاليكسين بوجود السبروفلوكساسين الذي يتداخل باطوال موجية 262-285.7 نانوميتر وبتراكيز مخ
... Show MoreFace Recognition Systems (FRS) are increasingly targeted by morphing attacks, where facial features of multiple individuals are blended into a synthetic image to deceive biometric verification. This paper proposes an enhanced Siamese Neural Network (SNN)-based system for robust morph detection. The methodology involves four stages. First, a dataset of real and morphed images is generated using StyleGAN, producing high-quality facial images. Second, facial regions are extracted using Faster Region-based Convolutional Neural Networks (R-CNN) to isolate relevant features and eliminate background noise. Third, a Local Binary Pattern-Convolutional Neural Network (LBP-CNN) is used to build a baseline FRS and assess its susceptibility to d
... Show MoreBackground: Unlike normal EEG patterns, the epileptiform abnormal pattern is characterized by different mor phologies such as the high-frequency oscillations (HFOs) of ripples on spikes, spikes and waves, continuous and sporadic spikes, and ploy2 spikes. Several studies have reported that HFOs can be novel biomarkers in human epilepsy study. S) Method: To regenerate and investigate these patterns, we have proposed three large scale brain network models (BNM by linking the neural mass model (NMM) of Stefanescu-Jirsa 2D (S-J 2D) with our own structural con nectivity derived from the realistic biological data, so called, large-scale connectivity connectome. These models include multiple network connectivity of brain regions at different
... Show MoreThis study includes replication and attenuation of foot and mouth disease virus type O which isolated from infected calves. Many passages for the virus in chick-Embryo were established as a substitute method to the tissue culture which is highly caustic in contrast to the chick embryo. The virus passed ten consequent passages which lead to the reduce of the titer of the virus from 106.53 TCID50/ 0.1 ml in cattle testis tissue culture to 103 TCID50/ 0.1 ml. the pathogenecity of attenuated FMD virus were also studied in both chick-embryo and guinea pigs. Using agar gel diffusion test precipitation antibodies was detected in guinea pig serum after 14 and 21 days post exposure to the attenuated virus. The inoculated guine
... Show MoreBackground : Hyperglycosylated hCG a newly discovered variant of hCG which can be used as a predictor of invasion of trophoblastic cells in patient with gestational trophoblastic disease. Objectives : To measure hyperglycosylated human chorionic gonadotrophin and to assess how far it can be used as predictor of invasion in invasive mole and choriocarcinoma. Study design control study. Setting: : Case Gynecological department in Baghdad Teaching Hospital from January 2016 to January 2017. Patient and Methods : 60 women were enrolled in this study 30 of them were with gestational trophoblastic disease (no.= 30 ) the remainder were normal pregnancy (no. =30) , hCG –H level was measured in both groups. Results : Mean serum hCG-H le
... Show MoreThe historical center's landscape suffers from neglect, despite their importance and broad capabilities in enhancing the cultural value of the historical center, as landscape includes many heterogeneous human and non-human components, material and immaterial, natural and manufactured, also different historical layers, ancient, modern and contemporary. Due to the difference in these components and layers, it has become difficult for the designer to deal with it. Therefore, the research was directed by following a methodology of actor-network theory as it deals with such a complex system and concerned with an advanced method to connect the various components of considering landscape as a ground that can include various elements and deal wi
... Show MoreThe expression of the Proprotein Convertase Subtilisin/Kexin Type 9 gene (PCSK9) is inextricably related to lipid levels and a risk of atherosclerotic coronary artery disease (ASCAD). The present study aims to measure the quantity of PCSK9 gene expression and the effect of methylation on its expression level taking part in the pathogenesis of acute coronary artery disorder.
A current study included 150 subjects from the Iraqi population, 100 ASCAD patients and 50 healthy controls. The concentration of PCSK9 in each serum sample was determined by the ELISA technique, the expression levels of the PCSK9 gene in whole blood were estimated by RT-qPCR – Quantitative Reverse Transcription PCR method, and DNA
... Show MoreIn this research, the semiparametric Bayesian method is compared with the classical method to estimate reliability function of three systems : k-out of-n system, series system, and parallel system. Each system consists of three components, the first one represents the composite parametric in which failure times distributed as exponential, whereas the second and the third components are nonparametric ones in which reliability estimations depend on Kernel method using two methods to estimate bandwidth parameter h method and Kaplan-Meier method. To indicate a better method for system reliability function estimation, it has be
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