Advancing Patient Safety: The Future of Artificial Intelligence in Mitigating Healthcare-Associated Infections: A Systematic Review.

ABSTRACT:

Background

Healthcare-associated infections are infections that patients acquire during hospitalization or while receiving healthcare in other facilities. They represent the most frequent negative outcome in healthcare, can be entirely prevented, and pose a burden in terms of financial and human costs. With the development of new AI and ML algorithms, hospitals could develop new and automated surveillance and prevention models for HAIs, leading to improved patient safety. The aim of this review is to systematically retrieve, collect, and summarize all available information on the application and impact of AI in HAI surveillance and/or prevention.

Methods

We conducted a systematic review of the literature using PubMed and Scopus to find articles related to the implementation

SUBMITTER: Radaelli D 

PROVIDER: S-EPMC11477207 | biostudies-literature | 2024 Oct

REPOSITORIES: biostudies-literature