One of the most Interesting natural phenomena is clouds that have a very strong effect on the climate, weather and the earth's energy balance. Also clouds consider the key regulator for the average temperature of the plant. In this research monitoring and studying the cloud cover to know the clouds types and whether they are rainy or not rainy using visible and infrared satellite images. In order to interpret and know the types of the clouds visually without using any techniques, by comparing between the brightness and the shape of clouds in the same area for both the visible and infrared satellite images, where the differences in the contrasts of visible image are the albedo differences, while in the infrared images is the temperature d

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,

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

Detection of early clinical keratoconus (KCN) is a challenging task, even for expert clinicians. In this study, we propose a deep learning (DL) model to address this challenge. We first used Xception and InceptionResNetV2 DL architectures to extract features from three different corneal maps collected from 1371 eyes examined in an eye clinic in Egypt. We then fused features using Xception and InceptionResNetV2 to detect subclinical forms of KCN more accurately and robustly. We obtained an area under the receiver operating characteristic curves (AUC) of 0.99 and an accuracy range of 97–100% to distinguish normal eyes from eyes with subclinical and established KCN. We further validated the model based on an independent dataset with

The aims of this reserch is identify  evaluate the organizational commitment level of (emotional, standard, continuous) and the level of discipline dimensions (functional duties, professional responsibility and ethics) for medical doctors in Ramadi Teaching Hospital due to their relationship with the organization effectiveness the level of completion work and the importance of the expected results in the field respondent

sample of (50) doctors has from all branches and specialties, including specialist doctors consultants and practitioners as well as branches of residence and senior the most prominent results reached are the emotional and the  st

Background: Prostatic adenocarcinoma is the most widely recognized malignancy in men and the second cause of cancer-related mortality encountered in male patients after lung cancer.

Aim of the study:  To assess the diagnostic value of diffusion weighted imaging (DWI) and its quantitative measurement, apparent diffusion coefficient (ADC), in the identification and localization of prostatic cancer compared with T2 weighted image sequence (T2WI).

Type of the study: a prospective analytic study

Patients and methods: forty-one male patients with suspected prostatic cancer were examined by pelvic MRI at the MRI department of the Oncology Teaching Hospital/Medical City in Baghdad

Objective: The study aimed to 1) measure the prevalence of depression and anxiety among Iraqi pharmacy and medical students at a number of universities in Baghdad using Hospital Anxiety and Depression Scale (HADS) and 2) investigate the association between various sociodemographic factors and students’ HADS scores. Methods: This study was based on a cross-sectional descriptive design in four universities in Baghdad, Iraq. Depression and anxiety were screened using an Arabic version of the HADS. An online survey was administered via Qualtrics to convenience samples of students at four colleges of pharmacy and a college of medicine between March and June 2018. Multiple linear regression was used to identify factors associated

Abstract:

It is essential to provide health care directly or indirectly based on laboratory tests in order of diagnosing diseases. There is an urgent need for the results of such tests to be accurate and reliable. Therefore, the International Organization for Standardization has prepared special standards for medical laboratories to prove their efficiency, presented in standards 15189: 2012. The aim of the research is to determine the possibility of the Al-alwiya Women's Hospital in meeting the requirements of the standards 15189: 2012, which includes administrative requirements consisting of fifteen items and technical requirements consisting of ten items. The research is important because laboratories shou