Personalized machine learning–based prognostic model for ICU-acquired bloodstream infections

We developed and externally validated a personalized ML-based prognostic model for ICU-BSIs using multicenter time-series data. This model may facilitate early identification of high-risk patients, enabling timely intervention and optimized ICU resource allocation.

Authors

Wanjun Liu (ORCID: https://orcid.org/0000-0001-6472-6247)
Xincheng Cai (ORCID: https://orcid.org/0009-0003-9116-9732)
Guomei Xia
Zhenhua Zhang (ORCID: https://orcid.org/0000-0002-8480-9004)
Xiujuan Yang
Yu Long
Chuanchang Wu
Shijun Zhou

Institutions

Anhui Medical University (CN)
Second Affiliated Hospital of Anhui Medical University (CN)

Publication Details

Journal: Frontiers in Cellular and Infection Microbiology
Published: 2025-10-29
DOI: https://doi.org/10.3389/fcimb.2025.1636886
Primary Topic: Sepsis Diagnosis and Treatment
Type: article
Field-Weighted Citation Impact: 0.00

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article

Personalized machine learning–based prognostic model for ICU-acquired bloodstream infections

Wanjun Liu, Xincheng Cai, Guomei Xia, Zhenhua Zhang et al.

Oct 29, 2025

Frontiers in Cellular and Infection Microbiology

Sepsis Diagnosis and Treatment

article

Personalized machine learning–based prognostic model for ICU-acquired bloodstream infections

Wanjun Liu, Xincheng Cai, Guomei Xia, Zhenhua Zhang, Xiujuan Yang, Yu Long, Chuanchang Wu, Shijun Zhou

October 29, 2025article en

Abstract

We developed and externally validated a personalized ML-based prognostic model for ICU-BSIs using multicenter time-series data. This model may facilitate early identification of high-risk patients, enabling timely intervention and optimized ICU resource allocation.

Frontiers in Cellular and Infection MicrobiologyVol. 15

Anhui Medical University (CN), Second Affiliated Hospital of Anhui Medical University (CN)

Openalex Percentile: Top 58%

Sepsis Diagnosis and Treatment

DOI Open Access PDF OpenAlex

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