The last few years witnessed great and increasing use in the field of medical image analysis. These tools helped the Radiologists and Doctors to consult while making a particular diagnosis. In this study, we used the relationship between statistical measurements, computer vision, and medical images, along with a logistic regression model to extract breast cancer imaging features. These features were used to tell the difference between the shape of a mass (Fibroid vs. Fatty) by looking at the regions of interest (ROI) of the mass. The final fit of the logistic regression model showed that the most important variables that clearly affect breast cancer shape images are Skewness, Kurtosis, Center of mass, and Angle, with an AUCROC of

Objectives: To highlight the knowledge of Al-Kindy medical students regarding varicella infection and to assess their knowledge and attitude toward its prevention. Methodology: This descriptive cross-sectional study enrolled academic year 2020/2021 students at Al-Kindy College of Medicine from first to final year. We used an online questionnaire by Google forms to collect data, which were analyzed with SPSS 26. Results: A total of 208 students participated with 126 in the preclinical and 82 in the clinical grades. Generally, most clinical students were more aware about epidemiology, clinical manifestations, and complications of varicella infection than the preclinical students. Conclusion: Educational stage is a significant variab

Breast cancer has got much attention in the recent years as it is a one of the complex diseases that can threaten people lives. It can be determined from the levels of secreted proteins in the blood. In this project, we developed a method of finding a threshold to classify the probability of being affected by it in a population based on the levels of the related proteins in relatively small case-control samples. We applied our method to simulated and real data. The results showed that the method we used was accurate in estimating the probability of being diseased in both simulation and real data. Moreover, we were able to calculate the sensitivity and specificity under the null hypothesis of our research question of being diseased o

-----

Background: Prostatic adenocarcinoma is the most widely recognized malignancy in men and the second cause of cancer-related mortality encountered in male patients after lung cancer.

Aim of the study:  To assess the diagnostic value of diffusion weighted imaging (DWI) and its quantitative measurement, apparent diffusion coefficient (ADC), in the identification and localization of prostatic cancer compared with T2 weighted image sequence (T2WI).

Type of the study: a prospective analytic study

Patients and methods: forty-one male patients with suspected prostatic cancer were examined by pelvic MRI at the MRI department of the Oncology Teaching Hospital/Medical City in Baghdad

Objectives: Assess nurses` practices for children with chemical poisoning, and find out relationship between nurses` socio- demographic data and their practices for children with chemical poisoning.

Methodology: A descriptive correlational design used to achieve the purpose of the study, the study was conducted at Al-Basrah Hospital for Maternal and Children throughout the period 12^th of September 2021 to 10^th of October 2022. A non- probability sample of (30) nurse at emergency department was selected. The instrument of the study was constructed based on previous literatures that related to study project, which include nurses` socio-demographic data and questionnaire format