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 diagnosing a tissue sample. Small, unnoticeable changes in pixel density may indicate the beginning of cancer or tear tissue in the early stages. These details even expert pathologists might miss. Artificial intelligence (A.I.) and D.L. revolutionized radiology by enhancing efficiency and accuracy of both interpretative and non-interpretive jobs. When you look at AI applications, you should think about how they might work. Convolutional Neural Network (C.N.N.) is a part of D.L. that can be used to diagnose knee problems. There are existing algorithms that can detect and categorize cartilage lesions, meniscus tears on M.R.I., offer an automated quantitative evaluation of healing, and forecast who is most likely to have recurring meniscus tears based on radiographs.
Objective(s): The study aims Finding relationship between UTI and demographic variable include: child's age, child's gender, if males are circumcised or not, child's order in his family, father's level of education, mother's level of education, place of residence and family socioeconomic status. Methodology: A descriptive study was conducted on students of primary schools for both sexes, for the period from 19th. February 2014 through to 4th March 2014. A selected sample from two steps the first stage is to choose a school by a stratified- cluster sample, getting schools that have been selected (12) sch
The goal (purpose) from using development technology that require mathematical procedure related with high Quality & sufficiency of solving complex problem called Dynamic Programming with in recursive method (forward & backward) through finding series of associated decisions for reliability function of Pareto distribution estimator by using two approach Maximum likelihood & moment .to conclude optimal policy
An experimental study was conducted with low cost natural waste adsorbent materials, barley husks and eggshells, for the removal of Levofloxacine (LEVX) antibacterial from synthetic waste water. Batch sorption tests were conducted to study their isothermal adsorption capacity and compared with conventional activated carbon which were, activated carbon > barley husks > eggshells with removal efficiencies 74, 71 and 42 % with adsorbents doses of 5, 5 and 50 g/L of activated carbon, barley husks, and eggshells respectively. The equilibrium sorption isotherms had been analyzed by Langmuir, Freundlich, and Sips models, and their parameters were evaluated. The experimental data were correlated well with the Langmuir model which gives the
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(12)
This paper presents the non-linear finite element method to study the behavior of four reinforced rectangular concrete MD beams with web circular openings tested under two-point load. The numerical finite elements methods have been used in a much more practical way to achieve approximate solutions for more complex problems. The ABAQUS /CAE is chosen to explore the behavior of MD beams. This paper also studies, the effect of both size and shape of the circular apertures of MD beams. The strengthening technique that used in this paper is externally strengthening using CFRP around the opening in the MD beams. The numerical results were compared to the experimental results in terms of ultimate load failure and displace
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(3)
Background: The incidence of maternal mortality in
placenta previa accrete is 7%,and its preoperative
diagnosis is of a great value.
Objective: to evaluate the efficacy of transabdominal
color Doppler ultrasound in diagnosing placenta
previa accreta and inccreta. Color Doppler imaging
criteria used in: includes diffuse parenchymal
placental lacunar flow, focal intra parenchymal
placental lacunar flow and bladder uterine serosa
interphase hyper-vascularity.
Design: Prospective study on patients from
January2007 to January 2008.
Patients and method: 48patients with one caesarean
section or more and with persistent anterior placenta
previa diagnosed by transabdominal ultrasound were
examined by c
Objectives: The aim of this study to assess instructional labor support behaviors among laboring
women in teaching hospitals in Hilla city.
Methodology: A descriptive analytic study was concluded to select a sample purposely of one hundred
multipara laboring women in maternity hospital in Hilla city and data was collected through
questionnaire form during February (1
st to March 30th) 2014. A descriptive statistical method was used
to analyze the data.
Results: The result showed that the highest percentage of study sample was at age (20-24) years, most
of them was house wife, more than third graduate from primary school, and more than half of them
lived in rural area, (86%) of study sample delivered normal deli
Objectives: The present study aimed to assess the compulsion among health care providers during the pandemic of COVID-19.
Methodology: a descriptive design was used in the present study. This study was conducted from October 10th, 2020 through May 20th, 2021. The study was conducted on a probability (convenient) sample of 248 physicians and nurses who work at Baghdad Teaching hospital in Baghdad city. The instrument was used in this study is the COVID Stress Scale-Arabic version (CSS).
Results: The result of this study showed that 42 % of HCPs had moderate symptoms and 36% of them had mild compulsive symptoms, and
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