Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D

Echocardiography is a widely used imaging technique to examine various cardiac functions, especially to detect the left ventricular wall motion abnormality. Unfortunately the quality of echocardiograph images and complexities of underlying motion captured, makes it difficult for an in-experienced physicians/ radiologist to describe the motion abnormalities in a crisp way, leading to possible errors in diagnosis. In this study, we present a method to analyze left ventricular wall motion, by using optical flow to estimate velocities of the left ventricular wall segments and find relation between these segments motion. The proposed method will be able to present real clinical help to verify the left ventricular wall motion diagnosis.

Lymphoma is a cancer arising from B or T lymphocytes that are central immune system ‎components. It is one of the three most common cancers encountered in the canine; ‎lymphoma affects middle-aged to older dogs and usually stems from lymphatic tissues, ‎such as lymph nodes, lymphoid tissue, or spleen. Despite the advance in the management of ‎canine lymphoma, a better understanding of the subtype and tumor aggressiveness is still ‎crucial for improved clinical diagnosis to differentiate malignancy from hyperplastic ‎conditions and to improve decision-making around treating and what treatment type to use. ‎This study aimed to evaluate a potential novel biomarker related to iron metabolism,

لمقدمة

     الحمد لله رب العالمين والصلاة والسلام على سيد الأنبياء والمرسلين نبينا محمد صلى الله عليه وسلم وعلى  واصحابه أجمعين  ومن تبعهم وأهتدى بهداهم الى يوم الدين اما بعد :

        فوظيفة القضاء وظيفة سامية يراد منها اقامة العدل ولا يستقيم حالهم الا به دفعاّ للظلم ، ولقد اولى النبي صلى الله عليه وآله وسلم ومن بعده الخلفاء الراشدون

Objective: The aim of this study is to determine the factors affecting birth space interval in a sample of women.
Methodology: A cross-sectional study conducted in primary health centers in Al-Tahade and Al- Shak Omar in
Baghdad city. Data were collected by direct interview using questionnaire especially prepared for the study.
Sample size was (415) women in age group (20-40) years who were chosen randomly.
Results: Analysis of data shows highest rate of women (31.8%) had a birth space interval of (8-12) months
followed by (26.7%) had a birth space interval of (19-24) months, (20.2%) had a birth space interval of (>24)
months and (16.1%) had a birth space interval of (13-18) months respectively, while lower rate of w

Background: Cystinosis is a rare autosomal recessive lysosomal storage disease with high morbidity and mortality. It is caused by mutations in the CTNS gene that encodes the cystine transporter, cystinosin, which leads to lysosomal cystine accumulation. It is the major cause of inherited Fanconi syndrome, and should be suspected in young children with failure to thrive and signs of renal proximal tubular damage. The diagnosis can be missed in infants, because not all signs of renal Fanconi syndrome are present during the first months of life. Elevated white blood cell cystine content is the cornerstone of the diagnosis. Since chitotriosidase (CHIT1 or chitinase-1) is mainly produced by activated macrophages both in normal and inflammator