COVID 19 has spread rapidly around the world due to the lack of a suitable vaccine; therefore the early prediction of those infected with this virus is extremely important attempting to control it by quarantining the infected people and giving them possible medical attention to limit its spread. This work suggests a model for predicting the COVID 19 virus using feature selection techniques. The proposed model consists of three stages which include the preprocessing stage, the features selection stage, and the classification stage. This work uses a data set consists of 8571 records, with forty features for patients from different countries. Two feature selection techniques are used in order to select the best features that affect the prediction of the proposed model. These are the Recursive Feature Elimination (RFE) as wrapper feature selection and the Extra Tree Classifier (ETC) as embedded feature selection. Two classification methods are applied for classifying the features vectors which include the Naïve Bayesian method and Restricted Boltzmann Machine (RBM) method. The results were 56.181%, 97.906% respectively when classifying all features and 66.329%, 99.924% respectively when classifying the best ten features using features selection techniques.
The study aimed at designing compound exercises using added weight on some skill abilities in youth soccer players aged (17 – 19) years old. The researcher sued the experimental method on (30) players aged (17 – 19) years old from Al Zawraa Sport Club. The subjects were divided into three groups and the training program was applied for (8) weeks with (3) training sessions per week. The data was collected and treated using proper statistical operations to conclude that compound exercises with weights between improved the subjects compared to the groups that did not use the added weights. Finally, the researchers recommended the necessity of using compound exercises using added weights during training sessions for youth soccer pla
... Show MorePolycystic ovary syndrome (PCOS) is the main cause of female infertility. The role of insulin resistance in the development of polycystic ovary is actively discussed here. The study included patients with PCOS without insulin resistance (n = 48) and with insulin resistance (n = 39). The comparison groups were patients with no history of PCOS: a control group without insulin resistance (n = 46) and a group of patients with insulin resistance (n = 45). The following parameters were determined in patients: FSH, LH, TSH, T3f, T4f, PRL, E2, 17-OHd, Pr, AMH, Test total, Testf, DHEAS, DHEASs, SHBG, ACTH, cortisol, IRI, IGF-1, C-peptide, and glucose level. The HOMA-IR index and the LH / FSH ratio and t
... Show MoreIn this paper, image compression technique is presented based on the Zonal transform method. The DCT, Walsh, and Hadamard transform techniques are also implements. These different transforms are applied on SAR images using Different block size. The effects of implementing these different transforms are investigated. The main shortcoming associated with this radar imagery system is the presence of the speckle noise, which affected the compression results.
Objective This research investigates Breast Cancer real data for Iraqi women, these data are acquired manually from several Iraqi Hospitals of early detection for Breast Cancer. Data mining techniques are used to discover the hidden knowledge, unexpected patterns, and new rules from the dataset, which implies a large number of attributes. Methods Data mining techniques manipulate the redundant or simply irrelevant attributes to discover interesting patterns. However, the dataset is processed via Weka (The Waikato Environment for Knowledge Analysis) platform. The OneR technique is used as a machine learning classifier to evaluate the attribute worthy according to the class value. Results The evaluation is performed using
... Show MoreThe relationship of hyperuricemia to kidney disease, diabetes, hypertension and the risk of cardiovascular diseases remain controversial. The aim of this study is to evaluate the use of uric acid (UA) levels to find the higher risk of cardiovascular disease (CVD) in patients with end stage renal disease that have diabetic nephropathy (DN), nephropathy with hypertension (NH) and patients with both diabetic nephropathy with hypertension (DNH). This study deals with 115 patients with end-stage renal disease under hemodialysis sub-grouped into 35 patients with (DN), 40 patients with (NH), and 40 patients with (DNH). Some biochemical parameters were determined in the serum of all participants such as HbA1c, fasting blood glucose (FBG), UA, urea,
... Show MorePeriodontal diseases (PD) are worldwide diseases of humans either in childhood or adults. The present study aimed to find the correlation between some demographic and saliva immunological factors including the determination of saliva TLR-2, IL6, CRP, and α- amylase in patients with periodontal diseases. For this purpose, 60 patients out of which 33were males and 27 were females participated in this study from different Dental treatment Centers (Amirya Specialized Dental Center and Almaamon Specialized Dental Center ) in Baghdad/ Iraq, for the period starting from November / 2021 to February / 2022. Both age ranges for patients and control are (13-70) years, and patients’ mean ages are 34.29±15.01. Additionally, the c
... Show MoreBackground: Hand, foot, and mouth disease is viral disease caused commonly by coxsackie virus A16 virus. It is a mild disease and children usually recover with no specific treatment within 7 to 10 days. Rarely, this illness may be associated with aseptic meningitis were patient may need hospitalization.
Objective: To determine significance of clinical features of hand, foot and mouth disease.
Methods: A cross sectional study of cases with clinical features of hand, foot and mouth disease visiting the dermatological consultation unit of Al Kindy teaching hospital. Sampling was for Zyona and Edressi Quarter patients over the period of 1st December 2017
... Show Morethe association between celiac disease and viral infection