Publications by authors named "M Omar Qadir"
Background: Based on the Fukuoka and Kyoto international consensus guidelines, the current clinical management of intraductal papillary mucinous neoplasm (IPMN) largely depends on imaging features. While these criteria are highly sensitive in detecting high-risk IPMN, they lack specificity, resulting in surgical overtreatment. Artificial Intelligence (AI)-based medical image analysis has the potential to augment the clinical management of IPMNs by improving diagnostic accuracy.
View Article and Find Full Text PDFMalic acid-derived polyamides, polyhydrazides, and hydrazides exhibit strong potential for a variety of biological applications. This study demonstrates the synthesis of cobalt, silver, copper, zinc, and iron particles by a facile chemical reduction approach utilizing malic acid-derived polyamides, polyhydrazides, and hydrazides as stabilizing and reducing agents. Comprehensive characterization of the particles was performed using UV-Vis spectroscopy, FTIR, XRD, SEM, and EDX analysis.
View Article and Find Full Text PDFPediatric thrombocytopenia is frequently observed in critical care and oncology settings with an increased risk of bleeding and platelet transfusions. However, little is known about low platelets in childhood during seasonal influence. This study aimed to evaluate the frequency and severity of pediatric thrombocytopenia in the postflood period.
View Article and Find Full Text PDFBackground: species are widely distributed in nature and found in various human body sites.
Objectives: To determine the antibiotic susceptibility pattern of species isolated from different clinical samples.
Methods: This cross-sectional study was conducted on 400 clinical specimens from conveniently sampled patients seeking healthcare at two health facilities in sulaimani / Iraq.
Article Synopsis
- Foamed concrete (FC) is popular in construction for being lightweight with excellent insulation, but predicting its compressive strength is difficult due to component interactions.
- This study utilized machine learning methods like decision trees and AdaBoost to enhance the accuracy of FC strength predictions, improving design optimization.
- The research processed 149 data points, showing the AdaBoost model significantly outperformed others with a correlation value (R) of 0.97, and included user-friendly software for practical application.