Objective: The aim of this study is to determine the factors affecting birth space interval in a sample of women.
Methodology: A cross-sectional study conducted in primary health centers in Al-Tahade and Al- Shak Omar in
Baghdad city. Data were collected by direct interview using questionnaire especially prepared for the study.
Sample size was (415) women in age group (20-40) years who were chosen randomly.
Results: Analysis of data shows highest rate of women (31.8%) had a birth space interval of (8-12) months
followed by (26.7%) had a birth space interval of (19-24) months, (20.2%) had a birth space interval of (>24)
months and (16.1%) had a birth space interval of (13-18) months respectively, while lower rate of w

Attention-Deficit Hyperactivity Disorder (ADHD), a neurodevelopmental disorder affecting millions of people globally, is defined by symptoms of hyperactivity, impulsivity, and inattention that can significantly affect an individual's daily life. The diagnostic process for ADHD is complex, requiring a combination of clinical assessments and subjective evaluations. However, recent advances in artificial intelligence (AI) techniques have shown promise in predicting ADHD and providing an early diagnosis. In this study, we will explore the application of two AI techniques, K-Nearest Neighbors (KNN) and Adaptive Boosting (AdaBoost), in predicting ADHD using the Python programming language. The classification accuracies obtained w

The manual classification of oranges according to their ripeness or flavor takes a long time; furthermore, the classification of ripeness or sweetness by the intensity of the fruit’s color is not uniform between fruit varieties. Sweetness and color are important factors in evaluating the fruits, the fruit’s color may affect the perception of its sweetness. This article aims to study the possibility of predicting the sweetness of orange fruits based on artificial intelligence technology by studying the relationship between the RGB values of orange fruits and the sweetness of those fruits by using the Orange data mining tool. The experiment has applied machine learning algorithms to an orange fruit image dataset and performed a co

    Artificial Neural Network (ANN) is widely used in many complex applications. Artificial neural network is a statistical intelligent technique resembling the characteristic of the human neural network.  The prediction of time series from the important topics in statistical sciences to assist administrations in the planning and make the accurate decisions, so the aim of this study is to analysis the monthly hypertension in Kalar for the period (January 2011- June 2018) by applying an autoregressive –integrated- moving average model  and artificial neural networks and choose the best and most efficient model for patients with hypertension in Kalar through the comparison between neural networks and Box- Je

This research discusses application Artificial Neural Network (ANN) and Geographical InformationSystem (GIS) models on water quality of Diyala River using Water Quality Index (WQI). Fourteen water parameterswere used for estimating WQI: pH, Temperature, Dissolved Oxygen, Orthophosphate, Nitrate, Calcium, Magnesium,Total Hardness, Sodium, Sulphate, Chloride, Total Dissolved Solids, Electrical Conductivity and Total Alkalinity.These parameters were provided from the Water Resources Ministryfrom seven stations along the river for the period2011 to 2016. The results of WQI analysis revealed that Diyala River is good to poor at the north of Diyala provincewhile it is poor to very polluted at the south of Baghdad City. The selected parameters wer

BACKGROUND: The degree of the development of coronary collaterals is long considered an alternate–that is, a collateral–source of blood supply to an area of the myocardium threatened with vascular ischemia or insufficiency. Hence, the coronary collaterals are beneficial but can also promote harmful (adverse) effects. For instance, the coronary steal effect during the myocardial hyperemia phase and that of restenosis following coronary angioplasty.

Background: Periodontal disease (PD) is a chronic inflammatory condition characterized by destruction of supporting structures of the teeth. Intelligence quotient (IQ) was potentially reported to significantly associated with prevalence of gingivitis. Mild gingivitis was obtained in high IQ levels while moderate gingivitis may be attributed to poor oral hygiene seen among the subjects having low IQ levels. Method: One hundred volunteers aged between 20-45 years old were enrolled in this study, patients were equally divided into right- and left-handed (50 patients each)and each group then subdivided into patients with healthy gingiva(10), patients with gingivitis (20), and patients suffering from periodontitis (20).An IQ questionnaire was p

Background: Pregnancy is considered a major risk factor for development and progression of periodontal disease. There are hormonal changes in both estrogen and progesterone hormones in addition to bacterial effect and poor oral hygiene that will enhance development of periodontal disease in pregnant women. Materials and methods: Seventy subjects were enrolled in the study, the subjects with an age range (20-35) years old without any history of systemic disease. The subjects were divided into 20 non-pregnant women they represent the control group (G I), 30 pregnant women with gingivitis (GII) and 20 pregnant women with periodontitis (GIII).All periodontal parameters (plaque index, gingival index, bleeding on probing, probing pocket depth an