Can Artificial Intelligence Optimize the Early Diagnosis of Invasive Candidiasis? A Systematic Review and Meta-Analysis.

ABSTRACT: The early diagnosis of invasive candidiasis remains challenging in immunocompromised and other high-risk patients, prompting interest in artificial intelligence models for assisting clinical decision-making. We conducted a PROSPERO-registered systematic review and meta-analysis of artificial intelligence-based predictive models for the early identification of invasive Candida infections. We searched multiple databases for studies reporting model performance in hospitalized immuno-compromised patients. Data on study characteristics, model details, validation strategy, and diagnostic accuracy were extracted. A bivariate random-effects meta-analysis was performed for candidemia prediction models with compatible data. Eight studies met inclusion criteria. Models were typically developed

SUBMITTER: Almeida H 

PROVIDER: S-EPMC12942343 | biostudies-literature | 2026 Feb

REPOSITORIES: biostudies-literature