Background: Psychiatry is an important branch of medicine and has been an integral part of the academic curriculum in Baghdad College of Medicine since its establishment. Medical students have a different attitude towards it as a medical profession like other specialties of medicine and as future medical career.

Objectives: This study aims to explore the attitudes of medical students towards psychiatry in general and as a future career after their course of clerkship in the Department of Psychiatry in Baghdad Teaching Hospital.

Patients and Methods: During the year 2016, 158 male and female students of fifth and sixth years participated in a brief five-question survey der

Objective- the study aim to determine the cardiac patient knowledge about anticoagulant medications using and its relationship with demographic data(age. gender. level of education. occupational). Methodology- A descriptive study(quasi-experimental)design was carried out to determine cardiac patient knowledge consider to using anticoagulant medications . Starting from(1th Jun 2017 to5th October 2018).To achieve the objectives of the study, a non-probability sample (a purposive sample) consisted of random sample comprised of (30) patients were taken anticoagulant medications ..The measurement of patient knowledge were collected through the use of questionnaire which is related to patient knowledge toward using the anticoagulant medication

 The extraction behaviour of a secondary amine (Dioctylamine) and a combination of secondary amine and tertiary amine (Tricapryl amine) toward some of the metal ions were investigated. Two types of diluents were applied, namely, mesitylene and treated Kerosene fraction. The extractability of dioctylamine and different combinations of tertiary amine and secondary amine toward uranium were investigated. The distribution coefficients and the separataion factors of uranium from the metal ions were calculated.

   Four hundred and fifty urine samples were collected from patients suffering from urinary tract infection from the General Azadi hospital in Kurkuk province ,during the period of october 2007 till march 2008 .       Results of bacteriological culture revealed that (168) out of (450) studied samples (37.3%) gave positive culture using blood agar and macConkey agar ; different species of bacterial isolates were detected using morphological and biochemical tests ,from these isolates the highest percentage of the isolates were from Escherichia coli when it was (100) isolates out of (190) isolate  (52.63%)  .  one hundred isolates were distributed between (77) from females and (23) from

During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve

User confidentiality protection is concerning a topic in control and monitoring spaces. In image, user's faces security in concerning with compound information, abused situations, participation on global transmission media and real-world experiences are extremely significant. For minifying the counting needs for vast size of image info and for minifying the size of time needful for the image to be address computationally. consequently, partial encryption user-face is picked. This study focuses on a large technique that is designed to encrypt the user's face slightly. Primarily, dlib is utilizing for user-face detection. Susan is one of the top edge detectors with valuable localization characteristics marked edges, is used to extract

The meniscus has a crucial function in human anatomy, and Magnetic Resonance Imaging (M.R.I.) plays an essential role in meniscus assessment. It is difficult to identify cartilage lesions using typical image processing approaches because the M.R.I. data is so diverse. An M.R.I. data sequence comprises numerous images, and the attributes area we are searching for may differ from each image in the series. Therefore, feature extraction gets more complicated, hence specifically, traditional image processing becomes very complex. In traditional image processing, a human tells a computer what should be there, but a deep learning (D.L.) algorithm extracts the features of what is already there automatically. The surface changes become valuable when

A nonlinear filter for smoothing color and gray images
corrupted by Gaussian noise is presented in this paper. The proposed
filter designed to reduce the noise in the R,G, and B bands of the
color images and preserving the edges. This filter applied in order to
prepare images for further processing such as edge detection and
image segmentation.
The results of computer simulations show that the proposed
filter gave satisfactory results when compared with the results of
conventional filters such as Gaussian low pass filter and median filter
by using Cross Correlation Coefficient (ccc) criteria.

The study conducted to investigate the association between Helicobacter pylori infection and eye diseases (Glaucoma, Cataract, CSR and Uveitis). One hundred and four patients with multiple eye disorders (10-80) years were observed from 10/9/2020 to 18/11/2020 and compared to thirty-one healthy people (19 female and 12 male). Each participant was tested for H. pylori CagAAbs and TNF-α using an enzyme-linked immunosorbent assay (ELISA). The results have shown that there was a non-significant difference (p≥0.05) in the concentration of CagAantibodies in sera of patients with eye diseases except in the case of CSR (central serous chorioretinopathy), which was a significant difference (P≤0.05) compared to the control group. Also, the result