The research aims to identify the rates of hair loss during pregnancy and lactation and its relation to the rates get some elements motivator urged through the results of the continued failure to meet the need of daily assessments of these elements, which led to the continuation of Hair Loss

Abstract:

              The hotel sector is one of the most vital sectors exposed to risks, and the authorities concerned with control must take their active and influential role in putting the hotel sector on the right track and compatible with the internationally approved approaches, and the importance of auditing the performance of the hotel sector in light of the (Covid-19) pandemic is embodied in the fact that it gives a clear and realistic picture to the management and regulatory bodies about the performance and activities of this sector and the shortcomings and deviations that must be addressed, and also helps government decision makers to ob

Medical images play a crucial role in the classification of various diseases and conditions. One of the imaging modalities is X-rays which provide valuable visual information that helps in the identification and characterization of various medical conditions. Chest radiograph (CXR) images have long been used to examine and monitor numerous lung disorders, such as tuberculosis, pneumonia, atelectasis, and hernia. COVID-19 detection can be accomplished using CXR images as well. COVID-19, a virus that causes infections in the lungs and the airways of the upper respiratory tract, was first discovered in 2019 in Wuhan Province, China, and has since been thought to cause substantial airway damage, badly impacting the lungs of affected persons.

Anemia in pregnancy can considerably elevate the maternal mortality risk and can negatively distress the development of fetus.

This cross-sectional, questionnaire-based study evaluated the knowledge, attitude and practice towards breast cancer and breast self-examination [‎BSE]‎ among 387 [‎302 females and 85 males]‎ educated Iraqis affiliated to 2 Iraqi universities. The participants were categorized into 3 occupations: student [‎71.3%]‎, teaching staff [‎10.3%]‎ and administrative staff [‎18.3%]‎. About half of the participants had a low knowledge score [‎< 50%]‎; only 14.3% were graded as [‎Good]‎ and above. Almost 75% of the participants believed that the best way to control breast cancer was through early detection and other possible preventive measures. Most participants [‎90.9%]‎ had heard of BSE, the main source of informatio

Objective: the aim of this study is to determine the level of students' knowledge about the environmental health.
Methodology: The cross-sectional study was conducted at the College of Health and Medical Technology in Baghdad
city during the period from 1st march till 1st of July 2012. Data was collected by self-recording of a previously designed
questionnaire to obtain socio-demographic information such as (age, gender, department, year of grade).
Results: The highest rate of students were in the 2nd year followed by the 3rd year, highest rate of students had low
level of knowledge followed by intermediate level of knowledge, while lowest rate of students on had high level of
knowledge .Females had higher level of know

<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol

<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol