Objectives: Determine the age and gender distribution of children who experience diabetes mellitus (DM) under
the age of 15 years and the presence of some associated factors that might be a predisposing factor for the
disease including obesity.
Methodology: A cross-sectional study was conducted at diabetic clinic in Children Welfare Teaching Hospital
in Baghdad City during 2006. The study sample included diabetic children less than 15 years of age. Data were
taken from the patients' record and by direct interview with the patients' parents. Information included
demographic data, as well as past history of the patient and his/her family relative to diabetes and other immune
diseases.
Results: Data analysis showed that there was an equal distribution of patients among the three age groups (I-5,
6-10-, and 11-15 years) in a rate of 33% for each. Females had higher incidence rate (660/o) than males. Onset of
the disease was mostly at age group I-3 years (32%) followed by age group 4-6 years (30%). IIistory of viral
illness was present in 24% of patients and a positive family history of DM was found in 23% of them, and a
family history of autoimmune disease was positive in 13% of cases. Body weight at the first visit to the clinic
was mainly below the 50th percentile (42% within the 25th percentile) and only 4% of patients had a body
weight within the 75th percentile.
Recommendations: Health education about the disease and provision of health centers those are easily
accessible for early diagnosis and treatment and uninerrupted insulin supply.
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The pancreatic ductal adenocarcinoma (PDAC), which represents over 90% of pancreatic cancer cases,
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In this paper, previous studies about Fuzzy regression had been presented. The fuzzy regression is a generalization of the traditional regression model that formulates a fuzzy environment's relationship to independent and dependent variables. All this can be introduced by non-parametric model, as well as a semi-parametric model. Moreover, results obtained from the previous studies and their conclusions were put forward in this context. So, we suggest a novel method of estimation via new weights instead of the old weights and introduce
Paper Type: Review article.
another suggestion based on artificial neural networks.
This paper includes a comparison between denoising techniques by using statistical approach, principal component analysis with local pixel grouping (PCA-LPG), this procedure is iterated second time to further improve the denoising performance, and other enhancement filters were used. Like adaptive Wiener low pass-filter to a grayscale image that has been degraded by constant power additive noise, based on statistics estimated from a local neighborhood of each pixel. Performs Median filter of the input noisy image, each output pixel contains the Median value in the M-by-N neighborhood around the corresponding pixel in the input image, Gaussian low pass-filter and Order-statistic filter also be used. Experimental results shows LPG-PCA method
... Show MoreMany authors investigated the problem of the early visibility of the new crescent moon after the conjunction and proposed many criteria addressing this issue in the literature. This article presented a proposed criterion for early crescent moon sighting based on a deep-learned pattern recognizer artificial neural network (ANN) performance. Moon sight datasets were collected from various sources and used to learn the ANN. The new criterion relied on the crescent width and the arc of vision from the edge of the crescent bright limb. The result of that criterion was a control value indicating the moon's visibility condition, which separated the datasets into four regions: invisible, telescope only, probably visible, and certai
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