The cancer is one of the biggest health problems that facing the world . And  the bladder cancer has a special place among the most spread cancers in Arab countries specially in Iraq and Egypt⁽²⁾ . It is one of the diseases which can be treated and cured if it is diagnosed early . This research is aimed at studying the assistant factors that diagnose bladder cancer such as (patient's age , gender , and other major complains of hematuria , burning or pain during urination and micturition disorders) and then determine which factors are the most effective in the possibility of diagnosing this disease by using the statistical model (logistic regression model) and depending on a random sample of (128) patients . After

Machine learning (ML) is a key component within the broader field of artificial intelligence (AI) that employs statistical methods to empower computers with the ability to learn and make decisions autonomously, without the need for explicit programming. It is founded on the concept that computers can acquire knowledge from data, identify patterns, and draw conclusions with minimal human intervention. The main categories of ML include supervised learning, unsupervised learning, semisupervised learning, and reinforcement learning. Supervised learning involves training models using labelled datasets and comprises two primary forms: classification and regression. Regression is used for continuous output, while classification is employed

Predicting peterophysical parameters and doing accurate geological modeling which are an active research area in petroleum industry cannot be done accurately unless the reservoir formations are classified into sub-groups. Also, getting core samples from all wells and characterize them by geologists are very expensive way; therefore, we used the Electro-Facies characterization which is a simple and cost-effective approach to classify one of Iraqi heterogeneous carbonate reservoirs using commonly available well logs.

The main goal of this work is to identify the optimum E-Facies units based on principal components analysis (PCA) and model based cluster analysis(MC

Keloids are prevalent fibro-proliferative tumors, and treating them is still a challenge although intralesional injections of triamcinolone acetonide (TAC) are effective, they have frequently linked adverse effects. Pentoxifylline (PTX) is an anti-fibrotic and anti-inflammatory, and vasodilator. It has not yet been tested for intralesional injection in keloids. The aim of the study is to study the efficacy of intralesional pentoxifylline versus triamcinolone acetonide in keloid scars of 40 patients. In this study, 40 patients with keloid scars regardless of the cause of keloid born, 20 patients have injected with intralesional triamcinolone acetonide, and 20 patients with intralesional pentoxifylline every two weeks until the lesi

The present work was aimed to form the baseline data of normal morphological and histological structure features of liver in migratory starling (Sturnus vulgaris). Anatomically, the starling liver bird was dark red -brown in colour and located in the cranial third of the abdominal cavity and consisted of undivided lobes (left and right). The liver right lobe was larger than the left. Histological examination revealed that the liver parenchyma was covered by a connective tissue capsule which appears to be thicker in the rim of liver lobes than other area in the liver lobe. Liver parenchyma was arranged in an unlimited hepatic lobules, which composed of polygonal hepatocytes organized as irregular, radial interconnecting cords or laminae of o