Background: Coping skills play a vital role in managing the physical and psychological effects of breast cancer (BC). Despite improvements in early detection and treatment, Breast cancer survivors continue to face long-term challenges after diagnosis. Therefore, this study aims to evaluate the coping skills employed by breast cancer women in Iraq and to identify the sociodemographic, clinical, and psychological factors associated with these coping skills. Methods: A cross-sectional study was conducted among 244 breast cancer women in The Medical City Teaching Oncology Hospital, Baghdad, Iraq, from August 2023 to October 2023, coping skills and psychological factors were assessed using the BRIEF COPE-28, and Hospital Anxiety Depression scale

Three hundred and fifty five patients with hepatitis were investigated in this study all cases gave negative result with HBs Ag , IgM-anti HCV , IgM-anti HEV, IgM-anti HDV and anti-HIV tests . The frequency of IgM-anti HAV was 113 and the percentage was 32 % in all ages but when these patients divided into five groups dependent on ages. The highest percentage of IgM-anti HAV was (45%) in age <10 and the percentage declined with age increase till to 9% in age >41 year.

Introduction and Aim: Graves ophthalmopathy is one of the pandemic public health disorders in Iraq. The current investigation attempts to determine the variation in the complete total blood cells on the recovery of individuals with Graves' ophthalmopathy following low and high-dose Radioactive Iodine 131 (RI-131) exposures.   Materials and Methods: The complete blood CBC level in people with Graves' illness and healthy, normal controls were quantitatively identified using the CBC counter. Thyroid stimulating hormone was utilized to compare the recovery of ophthalmopathy patients in comparison to a control group.    Results: In comparison to healthy controls, patients with Graves' ophthalmopathy disease who received 10 mci of RAI-

Unstable angina pectoris often leads to acute myocardial infarction. Since uric acid is thought to be risk factor for cardiovascular disease and considered a major antioxidant in human blood .The level of uric acid and lipid peroxidation in the sera of patients with unstable angina and myocardial infarction were measured and compared to the healthy individuals. Twenty-nine patients with unstable angina and twenty-nine patients with myocardial infarction were studied and compared to twenty-five healthy individuals. Uric acid was measured by using Human Kit. Malondialdelyde (MDA) a lipid peroxidation marker, was measured by thiobarbituric acid method .Significant elevation of uric acid and MDA were observed in the sera of pati

Background: Refractory/relapsed acute leukemia has always been a challenging problem for hematologist. Over the past decade emphasis has been made in the development of regimens containing fludarabine, combined with cytosine arabinoside for the treatment of refractory/relapsed acute leukemias. The aim of this study is to evaluate the efficacy and toxicity of the combination of fludarabine, high dose cytarabine, and granulocyte colony stimulating factor in refractory relapsed cases of acute leukaemia,
Methods: a prospective study is being conducted at the national center of hematology and hematology unit /Baghdad teaching hospital from July 2008 to July 2010.Twenty Patients with refractory/relapsed acute leukemia were treated with flud

Problem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a