What question did this study set out to answer?

The research aims to explore the burden of healthcare-associated infections (HAIs) and the application of AI in identifying susceptibility profiles in long-term care facilities (LTCFs).

April 10, 2026Open Access

Healthcare-associated infections in Italian long-term care facilities: a machine learning analysis of a 12-month cohort

Key Points

The research aims to explore the burden of healthcare-associated infections (HAIs) and the application of AI in identifying susceptibility profiles in long-term care facilities (LTCFs).
Analyzed a 12-month cohort of healthcare-associated infections in Italian LTCFs.
Utilized machine learning techniques for clustering analysis to identify infection susceptibility profiles.
Confirmed a high burden of healthcare-associated infections in Italian LTCFs.
Demonstrated that AI-based clustering can identify reproducible susceptibility profiles for HAIs.

Abstract

This study confirms the high burden of HAIs in Italian LTCFs and provides exploratory evidence that AI-based clustering can identify reproducible HAI susceptibility profiles in a setting where such approaches have been scarcely applied.

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Discussion

Authors

Anna Caterina Leucci

Elena Sasdelli

Luana Caselli

Journals

Infection Control and Hospital Epidemiology

Actions

Institutions

University of Padua

University of Turin

Agenzia Regionale Prevenzione e Ambiente della Regione Emilia-Romagna

References and Citations

Connected Papers

Building similarity graph...

Analyzing shared references across papers

Healthcare-associated infections in Italian long-term care facilities: a machine learning analysis of a 12-month cohort

Key Points

Abstract

Citation Network

Connected Papers

Discussion

Authors

Journals

Actions

Institutions

References and Citations

Citation Network

Connected Papers

Discussion

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