Polycystic ovarian syndrome, additionally called PCOS is the most widespread endocrine illness amongst women. The aetiology of PCOS is attributed to a multi-factorial interplay among environmental and genetic effects. The overarching goal evaluates the correlation among blood concentrations of total testosterone, sex-hormone-binding globulin (SHBG), estradiol (E2), follicle-stimulating hormone (FSH) and luteinizing hormone (LH) in ladies with PCOS and the impact of obesity, age, marital popularity on the obtained results. This study was conducted at the National Center for Educational Laborites /Medical City/ Baghdad. The study comprised of a sample of 83 women, elderly between 17 -45 years, who had been selected in a random manner

Leishmaniasis is a transmissible infection brought about by an obligatory intracellular protozoan from the genus Leishmania.  It occurs worldwide in tropical and subtropical regions and can be burdensome in resource-constrained countries. The infection ranges in severity from mild cutaneous lesions to more severe and sometimes life-threatening visceral and distorting mucocutaneous sicknesses. Importantly, cutaneous leishmaniasis (CL) is prevalent in the Middle East with a pooled prevalence of 12%. It imposes a significant health and socioeconomic burden

Background: The use of minerals in treatment of different diseases is as old as man himself. zinc is the most famous trace mineral related to male sexual function. Oligoasthenozoospermic subfertile patients were treated with zinc sulphate for three months.

Objectives: Aim of the research is to investigate the role of Zinc and if it affects the abnormalities of some semen parameters and to study the possible role of pharmaceutical preperations of zinc in amelioration of male subfertility as well as to assess the ability of Zinc to induce changes in the serum and semen zinc levels in addition to the levels of reproductive hormones (FSH and Testosterone).

Type of the study:

Background: This in vitro study evaluated the fracture resistance of weakened endodontically treated premolars with class II MOD cavities restored with different composite restorations (Low-shrinkage Filtek P90, nanohybrid Filtek Z250 XT and SDR bulk fill). The type and mode of fracture were also assessed for all the experimental groups. Materials and Method: Fifty human adult maxillary premolar teeth were selected for this study. Standardized extensive class II MOD cavities with endodontic treatment were prepared for all teeth, except those that were saved as intact control. The teeth were divided into five groups of ten teeth each (n=10): (Group 1) intact control group, (Group 2) unrestored teeth with endodontic treatment, (Group 3) resto

The objective of this study is to determination the content of some heavy metals (lead, cadmium, chromium) in colored tattoo stickers. twelve kinds of colored tattoo stikcers were collected from Baghdad markets, it was estimated heavy metals using atomic absorption spectrophotometer (Shimadzu A5000). The results indicated the concentrations of lead in all samples (1.61_1.00 mg / kg) and chromium in the three samples (0.85_0.97 mg / kg) while other samples are free of chromium , and cadmium. These elements are the components of printing inks and dyes in tattoo stickers, and this does not conform to the health and safety conditions for the packaging of food according to the organizations of the health and safety of

To determine the relationship between celiac disease and reproductive disorder, twenty two women with recurrent spontaneous abortion (18-35) years have been investigated from the period 2017/11/1 – 2018/2/1 and compared wih twenty two parentally healthy women. All studied groups were carried out to measure antitissue transglutaminase IgA and IgG antibodies by Enzyme linked immunosorbent assay (ELISA) technique, There were a highly significant differences (P < 0.01) in the concentration of anti TtG IgA and IgG Ab compared to control group, while there was non-significant differences (P > 0.05) in the concentration of anti TtG IgA according to the age group and there was a significant difference (P < 0.05) in the concentration of anti TtG I

Background: Chronic periodontitis is an inflammatory disease of tissues supporting the teeth. Salivary compositions have been most intensely studied as a potential marker for periodontal disease. In this study, analysis of saliva provides a simple and non-invasive method of evaluating the role of salivary IgA (s-IgA) levels in periodontal disease by detecting the level of (s-IgA) in patients with chronic periodontitis smokers and non smokers patients and correlate the mean (s-IgA) levels with clinical periodontal parameters Plaque index (PLI) gingival index (GI), probing pocket depth (PPD) and clinical attachment level (CAL). Materials and Methods: The study samples consists of (15) patients with chronic periodontitis who were non smokers (

Support vector machine (SVM) is a popular supervised learning algorithm based on margin maximization. It has a high training cost and does not scale well to a large number of data points. We propose a multiresolution algorithm MRH-SVM that trains SVM on a hierarchical data aggregation structure, which also serves as a common data input to other learning algorithms. The proposed algorithm learns SVM models using high-level data aggregates and only visits data aggregates at more detailed levels where support vectors reside. In addition to performance improvements, the algorithm has advantages such as the ability to handle data streams and datasets with imbalanced classes. Experimental results show significant performance improvements in compa

The interests toward developing accurate automatic face emotion recognition methodologies are growing vastly, and it is still one of an ever growing research field in the region of computer vision, artificial intelligent and automation. However, there is a challenge to build an automated system which equals human ability to recognize facial emotion because of the lack of an effective facial feature descriptor and the difficulty of choosing proper classification method. In this paper, a geometric based feature vector has been proposed. For the classification purpose, three different types of classification methods are tested: statistical, artificial neural network (NN) and Support Vector Machine (SVM). A modified K-Means clustering algorithm

Objective: Breast cancer is regarded as a deadly disease in women causing lots of mortalities. Early diagnosis of breast cancer with appropriate tumor biomarkers may facilitate early treatment of the disease, thus reducing the mortality rate. The purpose of the current study is to improve early diagnosis of breast by proposing a two-stage classification of breast tumor biomarkers fora sample of Iraqi women.

Methods: In this study, a two-stage classification system is proposed and tested with four machine learning classifiers. In the first stage, breast features (demographic, blood and salivary-based attributes) are classified into normal or abnormal cases, while in the second stage the abnormal breast cases are