Neuroimaging is a description, whether in two-dimensions (2D) or three-dimensions (3D), of the structure and functions of the brain. Neuroimaging provides a valuable diagnostic tool, in which a limited approach is used to create images of the focal sensory system by medicine professionals. For the clinical diagnosis of patients with Alzheimer's Disease (AD) or Mild Cognitive Impairs (MCI), the accurate identification of patients from normal control persons (NCs) is critical. Recently, numerous researches have been undertaken on the identification of AD based on neuroimaging data, including images with radiographs and algorithms for master learning. In the previous decade, these techniques were also used slowly to differentiate AD and MCI symptoms from structure classification methods. This review focuses on neuroimaging studies conducted to detect and classify AD, through a survey based on Google Scholar content. We explore the challenges of this field and evaluate the performance of these studies along with their negative aspects.
Fifty celiac disease (CD) patients (21 males and 29 females) with an age range of 2-35 years and 25 apparently healthy controls were investigated for 10 autoantibodies (anti-tissue transglutaminase IgA antibody; ATA, anti-tissue transglutaminase IgG antibody; ATG, anti-gliadine IgA antibody; AGA, anti-gliadine IgG antibody; AGG, anti-nuclear antibody; ANA, anti-double strand DNA antibody; AdsDNA, anti-thyroid peroxidase antibody; ATP, anti-phospholipid antibody; APP, anti-myeloperoxidase antibody; AMP and anti-proteinase 3 antibody; AP3) in their sera. Six autoantibodies (ATA, ATG, AGA, AGG, AMP and AP3) showed significant variations between CD patients and controls. The first four antibodies were not detected in sera of controls, while
... Show MoreDiabetes is considered by the World Health Organization (WHO) as a main health problem globally. In recent years, the incidence of Type II diabetes mellitus was increased significantly due to metabolic disorders caused by malfunction in insulin secretion. It might result in various diseases, such as kidney failure, stroke, heart attacks, nerve damage, and damage in eye retina. Therefore, early diagnosis and classification of Type II diabetes is significant to help physician assessments.
The proposed model is based on Multilayer Neural Network using a dataset of Iraqi diabetes patients obtained from the Specialized Center for Endocrine Glands and Diabetes Diseases. The investigation includes 282 samples, o
... Show MoreTo determine the important pathogenic role of celiac disease in triggering several autoimmune disease, thirty patients with Multiple Sclerosis of ages (22-55) years have been investigated and compared with 25 healthy individuals. All the studied groups were carried out to measure anti-tissue transglutaminase antibodies IgA IgG by ELISA test, anti-reticulin antibodies IgA and IgG, and anti-endomysial antibodies IgA and IgG by IFAT. There was a significant elevation in the concentration of anti-tissue transglutaminase antibodies IgA and IgG compared to control groups (P≤0.05), there was 4(13.33%) positive results for anti-reticulin antibodies IgA and IgG , 3(10%) positive results for anti-endomysial antibodies IgA and IgG . There were 4 pos
... Show MoreInterleukin -33 is a new member of the IL-1 superfamily of cytokines that is expressed mainly by stromal cells.Its expression is upregulated following pro-inflammatory stimulation. Aim of the present study was to assess the serum IL-33 level and its relationship with inflammatory biomarker CRP in Iraqi females patients with celiac disease. Thirty five patients with celiac disease (CD) and thirty healthy individuals as control group were enrolled in this study,their age ranged (20-35) year.Anti-Gliadin IgA ,IgG and Anti-Tissue IgA ,IgG were estimated in all subjects as diagnostic parameters .ESR and CRP were assayed as inflammatory biomarkers. IL-33 was determined in patients and control groups.
... Show MoreIntroduction: The association between acute stroke and
renal function is well known. The aim of this study is to
know which group of patients with acute stroke is more
likely to have undiagnosed Chronic Kidney Disease and
which risk factors are more likely to be associated with.
Methods:We studied 77 patients who were diagnosed to
have an acute stroke.Patients were selected between
April2011andJune 2011 using the " 4-variable
Modification of
Diet in Renal Disease Formula " which estimates
Glomerular Filtration Rate using four variables :serum
creatinine ,age ,race and gender.
Results :The study included 38 male and 39 females
patients ,aged (35-95) years. Glomerular Filtration Rate in
patients wi
AbstractOBJECTIVES: To evaluate the long-term remission efficacy and safety of isotretinoin in the treatment of Behcet's disease (BD). PATIENTS and METHODS: This single-blind, controlled therapeutic study was conducted in the Department of Dermatology and Venereology at Baghdad Teaching Hospital from February 2011 to January 2012. Thirty patients with BD were included in this work. Each patient received isotretinoin 20 mg orally once daily for 3 months. They were assessed at week 2 and then monthly depending on the Clinical Manifestation Index (CMI) and to record any side effects. At week 12, isotretinoin was stopped and patients were given placebo therapy in a form of glucose capsules for another 3 months. RESULTS: Thirty patients were tre
... Show MoreWith the rapid development of computers and network technologies, the security of information in the internet becomes compromise and many threats may affect the integrity of such information. Many researches are focused theirs works on providing solution to this threat. Machine learning and data mining are widely used in anomaly-detection schemes to decide whether or not a malicious activity is taking place on a network. In this paper a hierarchical classification for anomaly based intrusion detection system is proposed. Two levels of features selection and classification are used. In the first level, the global feature vector for detection the basic attacks (DoS, U2R, R2L and Probe) is selected. In the second level, four local feature vect
... Show MoreCassava, a significant crop in Africa, Asia, and South America, is a staple food for millions. However, classifying cassava species using conventional color, texture, and shape features is inefficient, as cassava leaves exhibit similarities across different types, including toxic and non-toxic varieties. This research aims to overcome the limitations of traditional classification methods by employing deep learning techniques with pre-trained AlexNet as the feature extractor to accurately classify four types of cassava: Gajah, Manggu, Kapok, and Beracun. The dataset was collected from local farms in Lamongan Indonesia. To collect images with agricultural research experts, the dataset consists of 1,400 images, and each type of cassava has
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