biostudies-literatureUnknown7(12)Abbas GH<h4>Objectives</h4>This systematic review evaluates artificial intelligence (AI)-based predictive models developed for early sepsis detection in adult hospitalized patients. It explores model types, input features, validation strategies, performance metrics, clinical integration, and implementation challenges.<h4>Data sources</h4>A systematic search was conducted across PubMed, Scopus, Web of Science, Google Scholar, and CENTRAL for studies published between January 2015 and March 2025.<h4>Study selection</h4>Eligible studies included those developing or validating AI models for adult inpatient sepsis prediction using electronic health record data and reporting at least one performance metric (area under the curve [AUC], sensitivity, specificity, or F1 score). Studies focusing on pediatricCritical care explorationse1360https://www.ebi.ac.uk/biostudies/studies/S-EPMC12685403biostudies-literatureArtificial Intelligence-Based Predictive Modeling for Early Detection of Sepsis in Hospitalized Patients: A Systematic Review and Meta-Analysis.PMC12685403Giri OAKhan NHAbbas GHSen PfalseArtificial Intelligence-Based Predictive Modeling for Early Detection of Sepsis in Hospitalized Patients: A Systematic Review and Meta-Analysis.<h4>Objectives</h4>This systematic review evaluates artificial intelligence (AI)-based predictive models developed for early sepsis detection in adult hospitalized patients. It explores model types, input features, validation strategies, performance metrics, clinical integration, and implementation challenges.<h4>Data sources</h4>A systematic search was conducted across PubMed, Scopus, Web of Science, Google Scholar, and CENTRAL for studies published between January 2015 and March 2025.<h4>Study selection</h4>Eligible studies included those developing or validating AI models for adult inpatient sepsis prediction using electronic health record data and reporting at least one performance metric (area under the curve [AUC], sensitivity, specificity, or F1 score). Studies focusing on pediatric2025-01-01T00:00:00Z2025 Dec2026-06-07T04:52:01.822Z2026-06-07T03:05:54.264ZS-EPMC126854034134816010.1097/CCE.0000000000001360