A5089717659- Transportation Planning and Optimization
- Traffic Prediction and Management Techniques
- Antibiotic Use and Resistance
- Traffic control and management
- Antibiotic Resistance in Bacteria
- Human Mobility and Location-Based Analysis
- Inflammatory Myopathies and Dermatomyositis
- Bacterial Identification and Susceptibility Testing
- Data Management and Algorithms
- Pesticide Exposure and Toxicity
- Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis
- Evacuation and Crowd Dynamics
- Nosocomial Infections in ICU
- Systemic Sclerosis and Related Diseases
Hanoi Medical University
2023-2024
HCMC Hospital of Dermato Venereology
2024
Thai Nguyen University
2023
National Hospital of Pediatrics
2023
De Montfort University
2017-2020
ITS (United Kingdom)
2017-2020
Purpose: Studies on the epidemiology of bloodstream infection (BSI) and antimicrobial resistance (AMR) are limited in Vietnam. Thus, present study aimed to elucidate BSI AMR BSI-causing bacteria Methods: Data regarding blood cultures from 2014 2021 were collected analyzed using chi-square test, Cochran–Armitage binomial logistic regression model. Results: Overall, 2405 (14.15%) positive during period. In total, 55.76% BSIs occurred patients aged ≥ 60 years. The male-to-female ratio with was...
This cross-sectional study investigated the antimicrobial resistance (AMR) patterns of gram-negative pathogens isolated from 4,789 hospitalized patients with lower respiratory tract infections (LRTIs). Of collected specimens, 1,325 (27.7%) tested positive for bacteria. Acinetobacter baumannii (38.6%), Pseudomonas aeruginosa (33.5%), Klebsiella pneumoniae (18.7%), Escherichia coli (5.6%), and aerogenes (3.5%) were most prevalent isolates. AMR analysis revealed high rates (79.9%-100%) A....
Travel time is a basic measure based on which intelligent transportation systems such as traveler information systems, traffic management public are developed. Although many methodologies have been proposed, they not yet adequately solved challenges associated with travel time, in particular, estimation for all links large and dynamic urban network still an open problem that needs addressing. Typically focus placed major roads motorways main city arteries but there increasing need to know...
This paper presents a method for modelling relationship between road segments using feed forward back-propagation neural networks. Unlike most previous papers that focus on travel time estimation of based its traffic information, we proposed the Neighbouring Link Inference Method (NLIM) can infer segment (link) from neighbouring segments. It is valuable links which do not have recent information. The learns link and parameters nearby sparse historical data. A data outlier detection Gaussian...