Background:

Diabetic retinopathy is an eye disease in diabetic patients due to damage to the small blood vessels in the retina due to high and low blood sugar levels. Accurate detection and classification of Diabetic Retinopathy is an important task in computer-aided diagnosis, especially when planning for diabetic retinopathy surgery. Therefore, this study aims to design an automated model based on deep learning, which helps ophthalmologists detect and classify diabetic retinopathy severity through fundus images. In this work, a deep convolutional neural network (CNN) with transfer learning and fine tunes has been proposed by using pre-trained networks known as Residual Network-50 (ResNet-50). The overall framework of the proposed

Background: The coronary atherosclerosis received a great concern from the clinical aspect, but its pathological aspect is deficient in Iraq.  

Objectives: To find a correlation between the type of the lesions that were grossly identified and their corresponding microscopical grades and Studying the effect of remodeling on preservation of the luminal area, 3) demonstrate the endothelial dysfunction in atherosclerosis.

Methods: fifty cases were gathered from the Medico-legal institute in Baghdad during the period from January to July 2004.The left anterior descending (LAD), left circumflex (LCX) and right coronary artery (RCA) from 50 postmortem cases were biopsied.

    In recent years, predicting heart disease has become one of the most demanding tasks in medicine. In modern times, one person dies from heart disease every minute. Within the field of healthcare, data science is critical for analyzing large amounts of data. Because predicting heart disease is such a difficult task, it is necessary to automate the process in order to prevent the dangers connected with it and to assist health professionals in accurately and rapidly diagnosing heart disease. In this article, an efficient machine learning-based diagnosis system has been developed for the diagnosis of heart disease. The system is designed using machine learning classifiers such as Support Vector Machine (SVM), Nave Bayes (NB), and K-Ne

         The objective of the present study is to compare the effect of insulin like growth factor-1 on the lipid profile in sera of diabetic patients with and without dyslipidemia having the same medical treatment and compared with healthy control. The study included three groups. The biochemical parameters which were measured include, fasting blood sugar(FBS), glycated hemoglobin (HbA1c), fasting insulin, insulin like growth factor-1(IGF-1),  lipid profile [Total cholesterol (Tc) , triglyceride(TG), high density lipoprotein cholesterol(HDL-c) ,low density lipoprotein-cholesterol (LDL-c)and very low density lipoprotein-cholesterol (VLDL-c)], Atherogenic index of plasma(AIP), insulin resistance(IR). The resu

Background: Diabetes and hypertension are related to cardiovascular risk factors and are possible to detect development of atherosclerosis in cardiovascular system, were can predict their effect and measurement by ultrasound and Doppler study. These risk factors included increased intima-media thickness, resistive index (RI) and pulsatility index (PI) of the right common carotid arteries. Method: We studied 20 patients with diabetes and hypertension, and 20 patients with diabetes only, were examine right carotid arteries for these two groups. In this sample we studied the Lumen diameter of the Rt. carotid arteries, Intima – media thickness (IMT), peak systolic velocity, end diastolic velocity, and Pulsatility index, Resistance index were

Background: Obesity is an evolving major health problem in both developed and developing countries. Traditional obesity indices as body mass index, waist circumference, waist-hip-ratio are well known measures to identify obese subjects, however, neck circumference as an index of upper-body obesity was found to be a simple and time-saving screening measure that can be used to identify obesity and the likelihood of developing metabolic syndrome in type 2 diabetic patients.
Aim: to investigate the relationship of neck circumference (NC) to obesity and metabolic syndrome in Iraqi subjects with type 2 diabetes.
Methods: The study group included 90 type 2 diabetic subjects (48 men and 42 women) aged 30-68 years. The subjects were those w

Background: Many cardiac diseases can cause cardiac hypertrophy developed by the established cardiac overload, such as long term of uncontrolled hypertension, valvuler disease or congenital anomaly and many more causes. If the cause of hypertrophy persists for long time it will generate heart failure, as a result changes in size, shape and function of the heart which refer as remodeling.
Objective: To investigate the types of remodeling in patients with heart failure, and study its relation with cardiac performance.
Patients and methods: The study included fifty normal individuals and fifty patients, only those patients who developed hypertrophy and failure were chosen. The study has included the measurements of many cardiac parame

Back ground: Two groups of diabetic patients ((the first include 20 patients complaining from diabetes mellitus alone, and the second include patients that
complain from both hypertension and diabetes mellitus)) were included in this study. These patients were chosen((from a large number of patients, with a proved
diagnosis, that are referred to the neurophysiology unit from the department of medicine)) to be of the same age group and gender, so that any of these two factors
can no longer be a source of any possible error in the results.
Patients & methods: The electrophysiological tests that were done to all of our patients include: sensory latency and sensory amplitude for the ulnar and sural
nerv