Objective This research investigates Breast Cancer real data for Iraqi women, these data are acquired manually from several Iraqi Hospitals of early detection for Breast Cancer. Data mining techniques are used to discover the hidden knowledge, unexpected patterns, and new rules from the dataset, which implies a large number of attributes. Methods Data mining techniques manipulate the redundant or simply irrelevant attributes to discover interesting patterns. However, the dataset is processed via Weka (The Waikato Environment for Knowledge Analysis) platform. The OneR technique is used as a machine learning classifier to evaluate the attribute worthy according to the class value. Results The evaluation is performed using

Background: Urinary tract infections (UTIs) and their complications such as Bladder cancer (Bl. C.) are a health growing problem worldwide. Objective: To shed light on this subject, present study was done to investigate relationship between recurrent urinary tract infection (RUTI) due to Escherichia coli (E. coli) and Bl. C.Type of study: Cross-sectional study. Methods: This study included 130 patients with RUTI, 50 patients with Bl. C. and 50 control of both sexes (aged 7-85 years) attending Al-Zahra Teaching Hospital in Al-Kut/Wassit governorate and Al-Harery Teaching Hospital of specialized surgeries/Baghdad. The patients were divided into two groups: the first group (n=130) included those who were suffering from recurrent UTI without

Introduction: Breast cancer is a significant global health concern, affecting millions of women worldwide. While advancements in diagnosis and treatment have improved survival rates, the impact of this disease extends beyond physical health. It also significantly influences a woman's lifestyle and overall well-being. Objectives: The current study intends to analyze the lifestyle of breast cancer patients who are receiving therapy or are being followed up at the Oncology Teaching Hospital in Medical City, Baghdad, Iraq. Method: The present study uses a descriptive design with an application of an evaluation approach. A convenience sample of 100 women with breast cancer was selected from the Teaching Oncology Hospital at the Medical C

Background: Bowel preparation prior to
colonic surgery usually includes antibiotic
therapy together with mechanical bowel
preparation which may cause discomfort to the
patients, prolonged hospitalization and water
& electrolyte imbalance.
Objective: to assess whether elective colon
and rectal surgery may be safely performed
without preoperative mechanical bowel
preparation.
Method: the study includes all patients who
had elective large bowel resection at Medical
City – Baghdad Teaching Hospital between
Feb, 2007 to Jan, 2010. Emergency operations
were not included. The patients were randomly
assigned to the 2 study groups (with or without
mechanical bowel preparation.
Results: A to

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

Background: The present study aimed to assess the distribution, prevalence, severity of malocclusion in Baghdad governorate in relation to gender and residency Materials and Methods: A multi-stage stratified sampling technique was used in this investigation to make the sample a representative of target population. The sample consisted of 2700 (1349 males and 1351 females) intermediate school students aged 13 years representing 3% of the total target population. A questionnaire was used to determine the perception of occlusion and orthodontic treatment demand of the students and the assessment procedures for occlusal features by direct intraoral measurement using veriner and an instrument to measure the rotated and displaced teeth. Results a

Abstract Objective: The underlying molecular basis of ischemic heart diseases (IHDs) has not yet been studied among Iraqi people. This study determined the frequency and types of some cardiovascular genetic risk factors among Iraqi patients with IHDs. Methods: This is a cross-sectional study recruiting 56 patients with acute IHD during a 2-month period excluding patients >50 years and patients with documented hyperlipidemia. Their ages ranged between 18 and 50 years; males were 54 and females were only 2. Peripheral blood samples were aspirated from all patients for troponin I and DNA testing. Molecular analysis to detect 12 common cardiovascular genetic risk factors using CVD StripAssay® (ViennaLab Diagnostics GmbH, Austria) was performed

  Cardiovascular diseases CVD are responsible for the majority of death in many countries, the term cardiovascular disease CVD includes several diseases such as: coronary artery diseases (angina, myocardial infaraction MI, atherosclerosis) and stroke. These diseases cause elevation of TC, TG, LDL, VLDL, and MDA levels in plasma and decrease of HDL levels and PON activity in plasma, because of elevation in lipid peroxidation (LPO) activity.  Catechins is a water extract of green tea composed of: (-)epicatchin EC, ECG, EGC, EGCG, (+) catechin C and GC, these compounds play great roles against chronic diseases such as CVD. The effect of catechins extract on the preceding biochemical parameters was investigated in 40 volunteer male