AIMC Topic: Cross Infection
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Response to the letter to the editor regarding "Assisting the Infection Preventionist: Use of Artificial Intelligence for Healthcare-Associated Infection Surveillance".
American journal of infection control
Jul 1, 2024
A Pilot Study of Deep Learning Models for Camera based Hand Hygiene Monitoring in ICU.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2023
Hand hygiene is key to preventing cross-infections in the Intensive Care Unit (ICU). Monitoring of hand washing activities can effectively increase the compliance of clinicians to hand hygiene. In this paper, we explored the feasibility of recognizin...
Deep learning based non-contact physiological monitoring in Neonatal Intensive Care Unit.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2022
Preterm babies in the Neonatal Intensive Care Unit (NICU) have to undergo continuous monitoring of their cardiac health. Conventional monitoring approaches are contact-based, making the neonates prone to various nosocomial infections. Video-based mon...
[Deep Learning-based Risk Prediction Model for Postoperative Healthcare-associated Infections].
Zhongguo yi xue ke xue yuan xue bao. Acta Academiae Medicinae Sinicae
Feb 1, 2022
Objective To develop a risk prediction model combining pre/intraoperative risk factors and intraoperative vital signs for postoperative healthcare-associated infection(HAI)based on deep learning. Methods We carried out a retrospective study based on ...
Machine learning for identifying resistance features of using whole-genome sequence single nucleotide polymorphisms.
Journal of medical microbiology
Nov 1, 2021
, a gram-negative bacterium, is a common pathogen causing nosocomial infection. The drug-resistance rate of is increasing year by year, posing a severe threat to public health worldwide. has been listed as one of the pathogens causing the global c...
Predicting outcomes in central venous catheter salvage in pediatric central line-associated bloodstream infection.
Journal of the American Medical Informatics Association : JAMIA
Mar 18, 2021
OBJECTIVE: Central line-associated bloodstream infections (CLABSIs) are a common, costly, and hazardous healthcare-associated infection in children. In children in whom continued access is critical, salvage of infected central venous catheters (CVCs)...
Construction of a Risk Prediction Model for Hospital-Acquired Pulmonary Embolism in Hospitalized Patients.
Clinical and applied thrombosis/hemostasis : official journal of the International Academy of Clinical and Applied Thrombosis/Hemostasis
Jan 1, 2021
The purpose of this study is to establish a novel pulmonary embolism (PE) risk prediction model based on machine learning (ML) methods and to evaluate the predictive performance of the model and the contribution of variables to the predictive perform...
Distribution of main Gram-positive pathogens causing bloodstream infections in United States and European hospitals during the SENTRY Antimicrobial Surveillance Program (2010-2016): concomitant analysis of oritavancin in vitro activity.
Journal of chemotherapy (Florence, Italy)
Sep 1, 2018
This study updates the distribution and trends of Gram-positive organisms causing bloodstream infections (BSIs) in the United States (US) and Europe during 2010-2016. In vitro activities of oritavancin and comparators were also evaluated. Staphylococ...
AI Tackles Hospital Infections: Machine Learning Is Helping Clinicians.
IEEE pulse
Jan 1, 2018
For Ashley Zappia (Figure 1), getting her hands dirty was part of her job. Even though she always tried to remain as clean as possible, her work as a nursing aide at a Southern California hospital required a lot of diapering, changing, and other hand...
Arden Syntax MLM Building Blocks for Microbiological Concepts and Their Application in Infection Surveillance.
Studies in health technology and informatics
Jan 1, 2017
BACKGROUND: The diagnosis - and hence definitions - of healthcare-associated infections (HAIs) rely on microbiological laboratory test results in specific constellations.
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