Ehssan Moglad
Biographic Data
| ID | 8401787 |
|---|---|
| NAME | Ehssan Moglad |
| GIVEN NAMES | Ehssan |
| FAMILY NAME | Moglad |
| SIGNATURE | MOGLAD E |
| AFFILIATIONS | Prince Sattam Bin Abdulaziz University |
| ORCID | 0000-0002-1076-9740 |
| VERIFIED | Yes |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 2 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2023 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
Machine learning based prediction of antimicrobial resistance in Klebsiella spp
Introduction Klebsiella species are well-recognized pathogens implicated in both healthcare-associated and community-acquired infections, and they contribute substantially to the global burden of antimicrobial resistance. In this study, we investigated the epidemiology, temporal resistance trends, multidrug resistance profiles, and the application of machine learning (ML) approaches to predict antimicrobial susceptibility among Klebsiella isolate…
Molecular insights into novel environmental strains of Klebsiella quasipneumoniae harboring different antimicrobial-resistance genes
Introduction The emergence of bacterial pathogens in environmental hosts represents a major risk to public health. This study aimed at characterizing seven novel environmental strains of K. quasipneumoniae using a genomic approach which was misidentified by phenotypic methods in a previous batch of 27 species thought to be K. pneumoniae . Methods Whole-genome sequencing was performed using the Illumina platform, and the generated raw reads were d…
No prominent works on this page.
Molecular insights into novel environmental strains of Klebsiella quasipneumoniae harboring different antimicrobial-resistance genes
Introduction The emergence of bacterial pathogens in environmental hosts represents a major risk to public health. This study aimed at characterizing seven novel environmental strains of K. quasipneumoniae using a genomic approach which was misidentified by phenotypic methods in a previous batch of 27 species thought to be K. pneumoniae . Methods Whole-genome sequencing was performed using the Illumina platform, and the generated raw reads were d…
Machine learning based prediction of antimicrobial resistance in Klebsiella spp
Introduction Klebsiella species are well-recognized pathogens implicated in both healthcare-associated and community-acquired infections, and they contribute substantially to the global burden of antimicrobial resistance. In this study, we investigated the epidemiology, temporal resistance trends, multidrug resistance profiles, and the application of machine learning (ML) approaches to predict antimicrobial susceptibility among Klebsiella isolate…
Antibiotic resistance (2 works) · Antibiotic Resistance in Bacteria (2 works) · Klebsiella pneumoniae (2 works) · Aerobactin (1 work) · Antibiotic Use and Resistance (1 work) · Antibiotics (1 work) · Antimicrobial (1 work) · Artificial neural network (1 work) · Bacterial Identification and Susceptibility Testing (1 work) · Biology (1 work)