Alzheimer's disease (AD) increasingly affects the elderly and is a major killer of those 65 and over. Different deep-learning methods are used for automatic diagnosis, yet they have some limitations. Deep Learning is one of the modern methods that were used to detect and classify a medical image because of the ability of deep Learning to extract the features of images automatically. However, there are still limitations to using deep learning to accurately classify medical images because extracting the fine edges of medical images is sometimes considered difficult, and some distortion in the images. Therefore, this research aims to develop A Computer-Aided Brain Diagnosis (CABD) system that can tell if a brain scan exhibits indications of Alzheimer's disease. The system employs MRI and feature extraction methods to categorize images. This paper adopts the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset includes functional MRI and Positron-Version Tomography scans for Alzheimer's patient identification, which were produced for people with Alzheimer's as well as typical individuals. The proposed technique uses MRI brain scans to discover and categorize traits utilizing the Histogram Features Extraction (HFE) technique to be combined with the Canny edge to representing the input image of the Convolutional Neural Networks (CNN) classification. This strategy keeps track of their instances of gradient orientation in an image. The experimental result provided an accuracy of 97.7% for classifying ADNI images.
This paper aims to propose a hybrid approach of two powerful methods, namely the differential transform and finite difference methods, to obtain the solution of the coupled Whitham-Broer-Kaup-Like equations which arises in shallow-water wave theory. The capability of the method to such problems is verified by taking different parameters and initial conditions. The numerical simulations are depicted in 2D and 3D graphs. It is shown that the used approach returns accurate solutions for this type of problems in comparison with the analytic ones.
Improved Merging Multi Convolutional Neural Networks Framework of Image Indexing and Retrieval
This paper proposes a new structure of the hybrid neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Weight parameters of the hybrid neural structure with its serial-parallel configuration are adapted by using the Back propagation learning algorithm. The ability of the proposed hybrid neural structure for nonlinear system has achieved a fast learning with minimum number
... Show MoreBackground/Objectives: The purpose of current research aims to a modified image representation framework for Content-Based Image Retrieval (CBIR) through gray scale input image, Zernike Moments (ZMs) properties, Local Binary Pattern (LBP), Y Color Space, Slantlet Transform (SLT), and Discrete Wavelet Transform (DWT). Methods/Statistical analysis: This study surveyed and analysed three standard datasets WANG V1.0, WANG V2.0, and Caltech 101. The features an image of objects in this sets that belong to 101 classes-with approximately 40-800 images for every category. The suggested infrastructure within the study seeks to present a description and operationalization of the CBIR system through automated attribute extraction system premised on CN
... Show MoreZM Al-Bahrani, Medico Legal Update, 2021
Background Cardiovascular disease (CVD) is a leading cause of death worldwide. Ischemic heart disease is a major cause of morbidity and mortality. Lack of blood supply to the brain can cause tissue death if any of the cerebral veins, carotid arteries, or vertebral arteries are blocked. An ischemic stroke describes this type of event. One of the byproducts of methionine metabolism, the demethylation of methionine, is homocysteine, an amino acid that contains sulfur. During myocardial ischemia, the plasma level of homocysteine (Hcy) increases and plays a role in many methylation processes. Hyperhomocysteinemia has only recently been recognized as a major contributor to the increased risk of cardiovascular disease (CVD) owing to its eff
... Show MoreTo determine the relationship between celiac disease and reproductive disorder, twenty two women with recurrent spontaneous abortion (18-35) years have been investigated from the period 2017/11/1 – 2018/2/1 and compared wih twenty two parentally healthy women. All studied groups were carried out to measure antitissue transglutaminase IgA and IgG antibodies by Enzyme linked immunosorbent assay (ELISA) technique, There were a highly significant differences (P < 0.01) in the concentration of anti TtG IgA and IgG Ab compared to control group, while there was non-significant differences (P > 0.05) in the concentration of anti TtG IgA according to the age group and there was a significant difference (P < 0.05) in the concentration of anti TtG I
... Show MoreThe present study aimed to evaluate the levels of total immunoglobulin E and percentage count of eosinophil in some of allergic disease. Blood sample collected from 210 patients (110 female, 100 male) with allergic disease (allergic asthma, allergic rhinitis, and urticaria) their age between 10-70 years and 50 healthy control their age between 23-52 years. A highly significant (P<0.01) increase in the mean serum total IgE in patients with asthma (503.54 ± 63.49 IU/ml), Allergic rhinitis (442.77 ± 95.76 IU/ml) and urticaria (489.53 ± 69.68 IU/ml) as a compared with healthy controls (23.67 ± 5.81 IU/ml).There was a significant difference in percentage count of eosinophil in patients groups allergic asthma 4.37 ± 0.52% ,allergic rhinitis
... Show MoreBackground: Chronic periodontitis is an inflammatory disease of tissues supporting the teeth. Salivary compositions have been most intensely studied as a potential marker for periodontal disease. In this study, analysis of saliva provides a simple and non-invasive method of evaluating the role of salivary IgA (s-IgA) levels in periodontal disease by detecting the level of (s-IgA) in patients with chronic periodontitis smokers and non smokers patients and correlate the mean (s-IgA) levels with clinical periodontal parameters Plaque index (PLI) gingival index (GI), probing pocket depth (PPD) and clinical attachment level (CAL). Materials and Methods: The study samples consists of (15) patients with chronic periodontitis who were non smokers (
... Show More