AIMC Topic: Fungemia

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Rapid Rule Out of Culture-Negative Bloodstream Infections by Use of a Novel Approach to Universal Detection of Bacteria and Fungi.

The journal of applied laboratory medicine Nov 20, 2018
BACKGROUND: Currently it can take up to 5 days to rule out bloodstream infection. With the low yield of blood cultures (approximately 10%), a significant number of patients are potentially exposed to inappropriate therapy that can lead to adverse eve...
Humans Anti-Infective Agents Time Factors Real-Time Polymerase Chain Reaction Bacteria Bacteremia Blood Culture Predictive Value of Tests Limit of Detection Bacterial Proteins Fungi Fungal Proteins Antimicrobial Stewardship DNA-Directed DNA Polymerase Fungemia
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Prediction of bacterial and fungal bloodstream infections using machine learning in patients undergoing chemotherapy.

European journal of cancer (Oxford, England : 1990) Jun 18, 2025
PURPOSE: This study aimed to develop a machine learning (ML) model to predict bloodstream infection (BSI) in chemotherapy patients.
Humans Neural Networks, Computer Machine Learning Retrospective Studies Female Aged Adult Male Middle Aged Neoplasms Antineoplastic Agents Bacteremia Fungemia
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The Development and Validation of a Machine Learning Model to Predict Bacteremia and Fungemia in Hospitalized Patients Using Electronic Health Record Data.

Critical care medicine Nov 1, 2020
OBJECTIVES: Bacteremia and fungemia can cause life-threatening illness with high mortality rates, which increase with delays in antimicrobial therapy. The objective of this study is to develop machine learning models to predict blood culture results ...
Humans Machine Learning Retrospective Studies Electronic Health Records Female Reproducibility of Results Risk Factors Hospitalization Aged Male Middle Aged Bacteremia Blood Culture Models, Statistical Fungemia
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