AIMC Topic: Wound Infection

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Linking Patient-Reported and Clinician-Assessed Wound Status via Chatbot-Based Digital Surveillance for Wound Infection: Retrospective Observational Study.

JMIR formative research
BACKGROUND: Digital wound monitoring has become increasingly feasible with the widespread use of smartphones and mobile messaging platforms. Although most previous studies have focused on chronic wounds and demonstrated the clinical benefits of remot...

High-content imaging and deep learning-driven detection of infectious bacteria in wounds.

Bioprocess and biosystems engineering
Fast and accurate detection of infectious bacteria in wounds is crucial for effective clinical treatment. However, traditional methods take over 24 h to yield results, which is inadequate for urgent clinical needs. Here, we introduce a deep learning-...

Identification of Microorganism in Infected Wounds by Positively Charged Selective Sensor Array and Deep Learning Algorithm.

Analytical chemistry
Microorganism are ubiquitous and intimately connected with human health and disease management. The accurate and fast identification of pathogenic microorganisms is especially important for diagnosing infections. Herein, three tetraphenylethylene der...

Impact of robotic and open surgery on patient wound complications in gastric cancer surgery: A meta-analysis.

International wound journal
This meta-analysis is intended to evaluate the effect of both robotic and open-cut operations on postoperative complications of stomach carcinoma. From the earliest date until June 2023, a full and systemic search has been carried out on four main da...

Exploring prevalence of wound infections and related patient characteristics in homecare using natural language processing.

International wound journal
We aimed to create and validate a natural language processing algorithm to extract wound infection-related information from nursing notes. We also estimated wound infection prevalence in homecare settings and described related patient characteristics...

Self-Taught Learning Based on Sparse Autoencoder for E-Nose in Wound Infection Detection.

Sensors (Basel, Switzerland)
For an electronic nose (E-nose) in wound infection distinguishing, traditional learning methods have always needed large quantities of labeled wound infection samples, which are both limited and expensive; thus, we introduce self-taught learning comb...

A Novel Feature Extraction Approach Using Window Function Capturing and QPSO-SVM for Enhancing Electronic Nose Performance.

Sensors (Basel, Switzerland)
In this paper, a novel feature extraction approach which can be referred to as moving window function capturing (MWFC) has been proposed to analyze signals of an electronic nose (E-nose) used for detecting types of infectious pathogens in rat wounds....

Phage and enzyme therapies in wound infections: From lab to bedside.

Chinese medical journal
Antibiotic-resistant (AR) bacterial wound infections (WIs) impose major burdens on healthcare systems, exacerbated by ineffective therapies and stalled antibiotic development. Phage therapy and phage-derived enzymes have gained traction as potent alt...

Predictive Risk Models for Wound Infection-Related Hospitalization or ED Visits in Home Health Care Using Machine-Learning Algorithms.

Advances in skin & wound care
OBJECTIVE: Wound infection is prevalent in home healthcare (HHC) and often leads to hospitalizations. However, none of the previous studies of wounds in HHC have used data from clinical notes. Therefore, the authors created a more accurate descriptio...

Photographic LVAD Driveline Wound Infection Recognition Using Deep Learning.

Studies in health technology and informatics
The steady increase in the number of patients equipped with mechanical heart support implants, such as left ventricular assist devices (LVAD), along with virtually ubiquitous 24/7 internet connectivity coverage is motive to investigate and develop re...