Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

Background: Although radiological diagnostic studies (RDS) are an important and acceptable part of medical practice, it is not without hazards. It is associated with increased risk of cancer. Unfortunately the typical and safe dose of each radiological examination is not known. Most of our knowledge of cancer risk comes from studies of survivors of those exposed to whole body radiation from atomic bomb in Hiroshima & Nagasaki, jobs associated with radiation exposure, Chernobyl survivors & patients treated with radiation therapy for cancer and other diseases.

 Objectives   To estimate radiation dose received by patients from diagnostic radiological examinations and lifetime

Background: Hypertension is a major global health concern that increases the risk of cardiovascular disease. Understanding the impact of age and treatment types on blood pressure control is essential for optimizing therapeutic strategies. Aim: This study aims to assess how different treatment types and patient age influence blood pressure control in hypertensive patients. Methodology: A binary logistic regression model was employed to analyze data from 48 patients diagnosed with hypertension. The study investigated the impact of two treatment regimens and patient age on the likelihood of achieving optimal blood pressure levels. The statistical significance of the findings was evaluated using chi-square tests and p-values. Results: T

Background: Leukemia is a broad term given to a group of malignant diseases characterized by diffuse replacement of bone marrow with proliferating leukocyte precursors. Chemotherapy has been increasingly used to treat malignant conditions. The systemic sequelae as a result of these immunosuppressive techniques induce many oral and dental complications. This study was conducted to evaluate the effect of chemotherapy on oral health status and activity of salivary alkaline phosphates enzyme in patients with acute lymphocytic leukemia. Materials and methods: The study groups included 28 patients with acute lymphocytic leukemia; they were under chemotherapy, aged 20-25 year old. The control group includes healthy subjects matching with study

: Partial purification of phosphoenolpyruvate carboxykinase (PEPCK) from type 2 diabetic patients sera take place using some purification steps such as participation with ammonium sulphate (55-80%) and filtered through dialysis, then ion exchange chromatography by DEAE sepharose anion column, gel filtration chromatography by sephadex G-100 column. In ion exchange step, there are four peak are obtained, the highest enzyme activity obtained by (0.4 M Nacl) with purification fold (2.18), yield (44.3) of enzyme and specific activity (13.5) mg/ng, which obtained a single peak by gel filtration chromatography, the degree of purification (5.34) fold, yield of enzyme (20%) with specific activity (33.109mg/ng). The purified enzyme had an optimum tem