AIMC Topic: Cross Infection

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[Deep Learning-based Risk Prediction Model for Postoperative Healthcare-associated Infections].

Zhongguo yi xue ke xue yuan xue bao. Acta Academiae Medicinae Sinicae
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
, 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
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
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)
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
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
BACKGROUND: The diagnosis - and hence definitions - of healthcare-associated infections (HAIs) rely on microbiological laboratory test results in specific constellations.