Alzheimer’s Disease (AD) is the most prevailing type of dementia. The prevalence of AD is estimated to be around 5% after 65 years old and is staggering 30% for more than 85 years old in developed countries. AD destroys brain cells causing people to lose their memory, mental functions and ability to continue daily activities. The findings of this study are likely to aid specialists in their decision-making process by using patients’ Magnetic Resonance Imaging (MRI) to distinguish patients with AD from Normal Control (NC). Performance evolution was applied to 346 Magnetic Resonance images from the Alzheimer's Neuroimaging Initiative (ADNI) collection. The Deep Belief Network (DBN) classifier was used to fulfill classification function. Weights were used to test the proposed method's recognition capacity, and the network was trained with a sample training set. As a result, this study offeres a new method for identifying Alzheimer's disease utilizing automated categorization. In tests, it performed admirably With 98.46% accuracy achieved for AD and NC studied classes when combining Gray Level Co-occurrence Matrix (GLCM) features with a DBN.
Periodontal diseases such as gingivitis and periodontitis are considered common diseases. This study is aimed to predicate these diseases using non-harmful specimens such as saliva throughout the detection of some parameters. In the beginning, a random 51 patients' saliva was collected from outpatients who suffered from different degrees of periodontal diseases. Concurrently, another 40 people who appeared to be healthy were collected, and both patients and healthy people were subjected to a questionnaire form and diagnosed by a specialist dentist. The results of this study revealed that there is no significant difference between males and females in infection with periodontal diseases. As well, smoking is not acting as the main f
... Show MoreThe diagnoses system of varicose disease has a good level of performance due to the complexity and uniqueness in patterns of vein of the leg. In addition, the patterns of vein are internal of the body, and its features are hard to duplicate, this reason make this method not easy to fake, and thus make it contains of a good features for varicose disease diagnoses. The proposed system used more than one type of algorithms to produce diagnoses system of varicose disease with high accuracy, in addition, this multi-algorithm technique based on veins as a factor to recognize varicose infection. The obtained results indicate that the design of varicose diagnoses system by applying multi- algorithms (Naïve Bayes and Back-Propagation) produced new
... Show MoreToxoplasmosis is an infection caused by Toxoplasma gondii that leads to abortion or hydrocephalus during pregnancy.One hundered and twenty two aborted women were selected for this study. Serum samples were collected form Al-Kadhmia and Kamal Al-Samari Hospitals,and laboratories around Baghdad, and tested for specific IgG and IgM anti-toxoplasma antibodies to confirm toxoplasmosis in those women by using ELISA test.The result recorded that 51(41.8%) women had antibodies against Toxoplasma gondii, 25(59.5%) women were positive for IgG, and 17(40.5%) women were positive forIgM, while 9(17.6%)women were positive for both.
It is widely accepted that early diagnosis of Alzheimer's disease (AD) makes it possible for patients to gain access to appropriate health care services and would facilitate the development of new therapies. AD starts many years before its clinical manifestations and a biomarker that provides a measure of changes in the brain in this period would be useful for early diagnosis of AD. Given the rapid increase in the number of older people suffering from AD, there is a need for an accurate, low-cost and easy to use biomarkers that could be used to detect AD in its early stages. Potentially, the electroencephalogram (EEG) can play a vital role in this but at present, no reliable EEG biomarker exists for early diagnosis of AD. The gradual s
... Show MoreBiosensor is defined as a device that transforms the interactions between bioreceptors and analytes into a logical signal proportional to the reactants' concentration. Biosensors have different applications that aim primarily to detect diseases, medicines, food safety, the proportion of toxins in water, and other applications that ensure the safety and health of the organism. The main challenge of biosensors is represented in the difficulty of obtaining sensors with accuracy, specific sensitivity, and repeatability for each use of the patient so that they give reliable results. The rapid diversification in biosensors is due to the accuracy of the techniques and materials used in the manufacturing process and the interrelationshi
... Show MoreAccurate emotion categorization is an important and challenging task in computer vision and image processing fields. Facial emotion recognition system implies three important stages: Prep-processing and face area allocation, feature extraction and classification. In this study a new system based on geometric features (distances and angles) set derived from the basic facial components such as eyes, eyebrows and mouth using analytical geometry calculations. For classification stage feed forward neural network classifier is used. For evaluation purpose the Standard database "JAFFE" have been used as test material; it holds face samples for seven basic emotions. The results of conducted tests indicate that the use of suggested distances, angles
... Show MoreAutism is a lifelong developmental deficit that affects how people perceive the world and interact with each others. An estimated one in more than 100 people has autism. Autism affects almost four times as many boys than girls. The commonly used tools for analyzing the dataset of autism are FMRI, EEG, and more recently "eye tracking". A preliminary study on eye tracking trajectories of patients studied, showed a rudimentary statistical analysis (principal component analysis) provides interesting results on the statistical parameters that are studied such as the time spent in a region of interest. Another study, involving tools from Euclidean geometry and non-Euclidean, the trajectory of eye patients also showed interesting results. In this
... Show MoreIn this work, satellite images for Razaza Lake and the surrounding area
district in Karbala province are classified for years 1990,1999 and
2014 using two software programming (MATLAB 7.12 and ERDAS
imagine 2014). Proposed unsupervised and supervised method of
classification using MATLAB software have been used; these are
mean value and Singular Value Decomposition respectively. While
unsupervised (K-Means) and supervised (Maximum likelihood
Classifier) method are utilized using ERDAS imagine, in order to get
most accurate results and then compare these results of each method
and calculate the changes that taken place in years 1999 and 2014;
comparing with 1990. The results from classification indicated that