Background: Breast cancer is the first one among Iraqi females. Most of them present later for diagnosis. Early detection center in tertiary hospital practice uses FNAB for early diagnosis. Publications on accuracy of this detection are scarce.

Objective:  To test the accuracy of FNAB in breast lump diagnosis.

Methods: Diagnostic test accuracy study, on 204 women with breast lump, attending the oncology department in 2017.

Results: Fine-needle aspiration biopsy diagnosis of histologically malignant cases were, malignant in 89 (87.3%), suspicious of malignancy in 5 (4.9%), and benign in 4 (3.9%). Complete sensitivity was 87.3%, and specificity

Due to severe scouring, many bridges failed worldwide. Therefore, the safety of the existing bridge (after contrition) mainly depends on the continuous monitoring of local scour at the substructure. However, the bridge's safety before construction mainly depends on the consideration of local scour estimation at the bridge substructure. Estimating the local scour at the bridge piers is usually done using the available formulae. Almost all the formulae used in estimating local scour at the bridge piers were derived from laboratory data. It is essential to test the performance of proposed local scour formulae using field data. In this study, the performance of selected bridge scours estimation formulae was validated and sta

Abstract

This study aims at investigating the effectiveness of the cooperative inquiry strategy in developing the achievement and development of mathematical communication skills of elementary school students. To achieve this aim, the experimental method was utilized. The study sample consisted of an experimental group (n = 34) and a control group (n = 31), which were randomly selected from primary schools. A Teacher's Guide for teaching a unit entitled "Statistics and Graphic Representations" for the sixth elementary graders in the first semester were devised. A (30) multiple-choice item achievement test distributed at the levels of (recall, comprehension, and application), as well as an (18) item mathematical c

The hydrological process has a dynamic nature characterised by randomness and complex phenomena. The application of machine learning (ML) models in forecasting river flow has grown rapidly. This is owing to their capacity to simulate the complex phenomena associated with hydrological and environmental processes. Four different ML models were developed for river flow forecasting located in semiarid region, Iraq. The effectiveness of data division influence on the ML models process was investigated. Three data division modeling scenarios were inspected including 70%–30%, 80%–20, and 90%–10%. Several statistical indicators are computed to verify the performance of the models. The results revealed the potential of the hybridized s

Autorías: Abdulsahıb Mohammed Muneer, Habeeb Sabhan Maytham, Kazim Abed Emad. Localización: Revista iberoamericana de psicología del ejercicio y el deporte. Nº. 1, 2021. Artículo de Revista en Psyke.