Early diagnosis and prognostic prediction of secondary bloodstream infections caused by Acinetobacter baumannii in critically ill patients by machine-learning algorithms

We developed two ML based models for predicting AB-sBSI risk and 30-day mortality. As a preliminary exploration, both models have been converted into accessible web tools. These tools are designed to assist clinicians in making informed decisions and promptly adjusting treatment strategies for critically ill patients.

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Publication Details

Journal
Frontiers in Cellular and Infection Microbiology
Published
2026-01-08
DOI
https://doi.org/10.3389/fcimb.2025.1667176
Citations
1
Primary Topic
Antibiotic Resistance in Bacteria
Type
article
Field-Weighted Citation Impact
21.79

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article

Early diagnosis and prognostic prediction of secondary bloodstream infections caused by Acinetobacter baumannii in critically ill patients by machine-learning algorithms

Hui Xu, Pingjuan Liu, Wenjia Gan, Y. Chen et al.
1 citations
Frontiers in Cellular and Infection Microbiology
Antibiotic Resistance in Bacteria
21.79
article

Early diagnosis and prognostic prediction of secondary bloodstream infections caused by Acinetobacter baumannii in critically ill patients by machine-learning algorithms

Hui Xu, Pingjuan Liu, Wenjia Gan, Y. Chen, Tangdan Ding, Peisong Chen, Xianling Zhou, Hengxin Chen
article en
1 citations

Abstract

We developed two ML based models for predicting AB-sBSI risk and 30-day mortality. As a preliminary exploration, both models have been converted into accessible web tools. These tools are designed to assist clinicians in making informed decisions and promptly adjusting treatment strategies for critically ill patients.

Frontiers in Cellular and Infection MicrobiologyVol. 15
Sun Yat-sen University (CN), The First Affiliated Hospital, Sun Yat-sen University (CN), Third Affiliated Hospital of Sun Yat-sen University (CN)
National Natural Science Foundation of China, Natural Science Foundation of Guangdong Province
Good health and well-being
Openalex Percentile: Top 3%
Antibiotic Resistance in Bacteria
21.79
DOIOpen Access PDFOpenAlex
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Early diagnosis and prognostic prediction of secondary bloodstream infections caused by Acinetobacter baumannii in critically ill patients by machine-learning algorithms — Hui Xu, Pingjuan Liu, et al. · Frontiers in Cellular and Infection Microbiology (2026) | TGRS Research Map | TGRS