Heart disease is a significant and impactful health condition that ranks as the leading cause of death in many countries. In order to aid physicians in diagnosing cardiovascular diseases, clinical datasets are available for reference. However, with the rise of big data and medical datasets, it has become increasingly challenging for medical practitioners to accurately predict heart disease due to the abundance of unrelated and redundant features that hinder computational complexity and accuracy. As such, this study aims to identify the most discriminative features within high-dimensional datasets while minimizing complexity and improving accuracy through an Extra Tree feature selection based technique. The work study assesses the efficac

The continuous advancement in the use of the IoT has greatly transformed industries, though at the same time it has made the IoT network vulnerable to highly advanced cybercrimes. There are several limitations with traditional security measures for IoT; the protection of distributed and adaptive IoT systems requires new approaches. This research presents novel threat intelligence for IoT networks based on deep learning, which maintains compliance with IEEE standards. Interweaving artificial intelligence with standardization frameworks is the goal of the study and, thus, improves the identification, protection, and reduction of cyber threats impacting IoT environments. The study is systematic and begins by examining IoT-specific thre

Background: Toll-like receptors (TLRs) play a significant role in the activation of adaptive immunity and may have an essential role in the development of rheumatoid arthritis (RA). Objectives: To assess the gene expression of TLR4 in individuals with RA compared to healthy individuals. Methods: From July to December 2022. A total of 100 individuals were encompassed in the study, consisting of 50 individuals diagnosed with RA, of whom 42 were females and 8 were males, with an average age of 45.22 years. Additionally, there were 50 healthy control participants, 40 of whom were females and 10 were males, with an average age of 45.64 years. To assess the TLR4 transcript levels, blood samples were collected from each participant, and RN

AW Ali T, Journal of the Faculty of Medicine, 2015 - Cited by 3

Objective: Pregnancy-induced hypertension (PIH) is a major pregnancy complication that leads to maternal mortality. Here, we have scrutinized the correlation between serum levels of hydrogen peroxide (H2O2) and superoxide dismutase (SOD) in PIH.Methods: Serum samples were collected from 80 Iraqi women (40 women with PIH as patients group, 20 normotensive pregnant women as a positive control, and 20 normotensive non-pregnant women as a negative control) all groups were diagnosed clinically.Results: Serum of H2O2 and SOD levels was measured for all studied groups. Results showed that there were no significant variances in age and gestational age distribution between all studied groups. Furthermore, result showed that the serum level o