Disease diagnosis with computer-aided methods has been extensively studied and applied in diagnosing and monitoring of several chronic diseases. Early detection and risk assessment of breast diseases based on clinical data is helpful for doctors to make early diagnosis and monitor the disease progression. The purpose of this study is to exploit the Convolutional Neural Network (CNN) in discriminating breast MRI scans into pathological and healthy. In this study, a fully automated and efficient deep features extraction algorithm that exploits the spatial information obtained from both T2W-TSE and STIR MRI sequences to discriminate between pathological and healthy breast MRI scans. The breast MRI scans are preprocessed prior to the feature

Toxoplasmosis is a widespread infection usually caused by Toxoplasma gondii (T. gondii) parasite. It occurs in humans and other warm blooded animals, causing severe problems. It was found that there is an alteration in the trace elements concentrations levels associated with some human diseases. This study aimed to investigate the changes in the concentrations of some trace elements (Mg, Fe , Zn, and Cu) in the sera of 60 immunocompetent patients with chronic toxoplasmosis and 82 healthy individuals as a control group. Measuring the serum level of seropositivity rate of anti-T. gondii antibodies was done by Enzyme Linked Immunosorbent Assay (ELISA) Kit, while the concentrations of trace elements were measured by absorption spectrophotometry

Background: Recent research indicates that persistent inflammatory responses may contribute to the rise of diabetic nephropathy (DN) and diabetic cardiovascular disease (DCVD) in type 2 diabetes mellitus patients (DM2). Numerous molecules associated with inflammation and angiogenesis have been implicated in the development and progression of DN and DCVD, respectively. Methods: The subjects were separated into five groups: healthy controls (n= 25), type 2 diabetes mellitus patients (n= 30), type 2 diabetes mellitus patients with nephropathy DN (n= 30), and type 2 diabetes mellitus patients with cardiovascular disease DCVD (n= 30). The blood levels of irisin, IL-8, HbA1C, urea, and creatinine were determined. Results: In current study there w

The current study aimed to isolate and diagnose the fungi associated with the inflammatory bowel disease patients with 150 samples distributed between 50 samples from Crohn's patients and 50 samples from ulcerative colitis patients, 50 control from Al-Kindy Al Teaching Hospital in Baghdad, Baghdad. Five types of yeast were isolated and identified, namely C. albicans, C.glabarta, Tropicales, C. parapsilosis, C. and C., krusi C. parapsilosis and.and Aspergillus, Penicillium, Muocer, Rhizopous, Saccharomycosis, and Cryptococcus, The results indicated the dominance of Candida spp. In crohn’s disease, the frequency of isolated Candida albicans was 24 (58.54%), Candida glabrata 11 (26.86%), Candida tropicalis 5 (12.2%) and Candida krusi was 1 (

The aim of this study is to find a relationship between oxidative stress and adiponectin in Iraqi patients with acromegaly. The present study included 30 patients with acromegaly disease attending at Al-Yarmuk teaching hospital , and 30 healthy individuals as a control group.The two groups with ages ranging (30-55) years. The results revealed a highly significant elevation in all parameters (GH,IGF-1 , adiponectin , malondialdehyde , and peroxynitrite ) levels in sera of patients when compared with healthy control .It can be concluded that oxidative stress (malondialdehyde and peroxynitrite ) may be valuable in detecting of endocrine diseases like acromegaly .