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  4. Vol 5, Issue 1, 2025

Research progress on the application of learning algorithms in risk assessment of ICU-acquired infections in the intensive care unite

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DOI: 10.23977/phpm.2025.050105 | Downloads: 13 | Views: 478

Author(s)

Chen Huaqi 1, Liu Qiong 1

Affiliation(s)

1 Department of Emergency, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China

Corresponding Author

Liu Qiong

ABSTRACT

ICU-acquired infections is a significant challenge for critically ill patients in the Intensive Care Unit (ICU), and the early identification of infections and timely clinical interventions are crucial for improving patient outcomes. With the increasing prevalence of artificial intelligence (AI), machine learning has been widely applied in clinical practice, including disease diagnosis and prognostic risk assessment. This review aims to systematically summarize the research progress on ICU-acquired infection risk prediction models based on machine learning, in order to provide valuable evidence for clinical practice and references for future related studies.

KEYWORDS

ICU-acquired infections; machine learning; clinical prediction model; reviews

CITE THIS PAPER

Chen Huaqi, Liu Qiong, Research progress on the application of learning algorithms in risk assessment of ICU-acquired infections in the intensive care unite. MEDS Public Health and Preventive Medicine (2025) Vol. 5: 26-32. DOI: http://dx.doi.org/10.23977/phpm.2025.050105.

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