Applications of artificial intelligence in emergency and critical care diagnostics: a systematic review and meta-analysis.

Introduction: Artificial intelligence has come to be the highlight in almost all fields of science. It uses various models and algorithms to detect patterns and specific findings to diagnose a disease with utmost accuracy. With the increasing need for accurate and precise diagnosis of disease, employing artificial intelligence models and concepts in healthcare setup can be beneficial. Methodology: The search engines and databases employed in this study are PubMed, ScienceDirect and Medline. Studies published between 1st January 2013 to 1st February 2023 were included in this analysis. The selected articles were screened preliminarily using the Rayyan web tool, after which investigators screened the selected articles individually. The risk of bias for the selected studies was assessed using QUADAS-2 tool specially designed to test bias among studies related to diagnostic test reviews. Results: In this review, 17 studies were included from a total of 12,173 studies. These studies were analysed for their sensitivity, accuracy, positive predictive value, specificity and negative predictive value in diagnosing barrette's neoplasia, cardiac arrest, esophageal adenocarcinoma, sepsis and gastrointestinal stromal tumors. All the studies reported heterogeneity with p-value <0.05 at confidence interval 95%. Conclusion: The existing evidential data suggests that artificial intelligence can be highly helpful in the field of diagnosis providing maximum precision and early detection. This helps to prevent disease progression and also helps to provide treatment at the earliest. Employing artificial intelligence in diagnosis will define the advancement of health care environment and also be beneficial in every aspect concerned with treatment to illnesses.

An X-STRs analysis of the Iraqi Sorani Kurds.

A database for the Iraqi Sorani Kurds, specifically focused on the 12 X-short tandem repeat (STR) loci, has been developed to fascilitate forensic and population genetics investigations. The present study involved genotyping 117 unrelated individuals from the Sorani Kurds ethnic group using the Investigator Argus X-12 QS kit. The analysis revealed that the DXS10135 locus exhibited the highest degree of polymorphism, as indicated by a polymorphism information content (PIC) value of 0.94565 and a gene diversity (GD) value of 0.95623. Conversely, the DXS8378 locus displayed the lowest level of polymorphism, with a PIC value of 0.61026 and a GD value of 0.68170. Notably, two individuals were found to possess a rare allele (allele = 6) at the DXS8378 locus, which was not included in the allelic ladder of the kit. Furthermore, a significant linkage disequilibrium (LD) (p < 0.05/117) was observed between the DXS10103 and DXS10101 loci on linkage group 3 (LG3). The ancestral composition of the five primary geographic regions, namely Africa, Middle East, East Asia, Europe, and South America, was determined through the utilization of the [Formula: see text] ratio. The findings of this analysis revealed that the Middle Eastern populations exhibited the lowest [Formula: see text] ratio, measuring at 0.23243, indicating a relatively lower ancestral diversity. Conversely, the European populations showcased the highest [Formula: see text] ratio, measuring at 0.27122, indicative of a greater ancestral diversity within this region. Additionally, the allelic richness indicators, namely distinctive and private alleles, indicated that Africa and the Middle East displayed the highest levels, while Far East Asia exhibited the lowest. This analysis supports the hypothesis of repeated founder effects during outward migrations, as evidenced by both the ancestry variability and the allelic richness. Consequently, the findings of this study have important implications for forensic genetics and population genetics research, particularly in relation to the consideration of genetic predispositions within specific ethnic groups.

The Qatari population's genetic structure and gene flow as revealed by the Y chromosome.

The Y-chromosome has been widely used in forensic genetic applications and human population genetic studies due to its uniparental origins. A large database on the Qatari population was created for comparison with other databases from the Arabian Peninsula, the Middle East, and Africa. We provide a study of 23 Y-STR loci included in PowerPlex Y23 (Promega, USA) that were genotyped to produce haplotypes in 379 unrelated males from Qatar, a country at the crossroads of migration patterns. Overall, the most polymorphic locus provided by the Promega kit was DYS458, with a genetic diversity value of 0.85 and a haplotype diversity of 0.998924. Athey's Haplogroup Predictor tool was used to predict haplogroups from Y-STR haplotypes in the Qatari population. In a median-joining network, the haplogroup J1 predominance (49%) in Qatar generated a star-like expansion cluster. The graph of population Q-matrix was developed using Y-STR data from 38 Middle Eastern and 97 African populations (11,305 individuals), and it demonstrated a stronger sub-grouping of countries within each ethnic group and showed the effect of Arabs on the indigenous Berbers of North Africa. The estimated migration rate between the Qatari and other Arabian populations was inferred using Bayesian coalescence theory in the Migrate-n program. According to the Gene Flow study, the main migration route was from Yemen to Kuwait through Qatar. Our research, using the PowerPlex Y23 database, shows the importance of gene diversity, as well as regional and social structuring, in determining the utility of demographic and forensic databases.