{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,6]],"date-time":"2026-05-06T00:42:32Z","timestamp":1778028152808,"version":"3.51.4"},"reference-count":50,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2024,3,28]],"date-time":"2024-03-28T00:00:00Z","timestamp":1711584000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001871","name":"FCT and IP","doi-asserted-by":"publisher","award":["RISE-LA\/P\/0053\/2020"],"award-info":[{"award-number":["RISE-LA\/P\/0053\/2020"]}],"id":[{"id":"10.13039\/501100001871","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001871","name":"FCT and IP","doi-asserted-by":"publisher","award":["UIDP\/4255\/2020"],"award-info":[{"award-number":["UIDP\/4255\/2020"]}],"id":[{"id":"10.13039\/501100001871","id-type":"DOI","asserted-by":"publisher"}]},{"name":"FCT\u2014Funda\u00e7\u00e3o para a Ci\u00eancia e a Tecnologia, I.P., within CINTESIS","award":["RISE-LA\/P\/0053\/2020"],"award-info":[{"award-number":["RISE-LA\/P\/0053\/2020"]}]},{"name":"FCT\u2014Funda\u00e7\u00e3o para a Ci\u00eancia e a Tecnologia, I.P., within CINTESIS","award":["UIDP\/4255\/2020"],"award-info":[{"award-number":["UIDP\/4255\/2020"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Antibiotics"],"abstract":"<jats:p>Antimicrobial resistance (AMR) is a growing public health problem in the One Health dimension. Artificial intelligence (AI) is emerging in healthcare, since it is helpful to deal with large amounts of data and as a prediction tool. This systematic review explores the use of AI in antimicrobial stewardship programs (ASPs) and summarizes the predictive performance of machine learning (ML) algorithms, compared with clinical decisions, in inpatients and outpatients who need antimicrobial prescriptions. This review includes eighteen observational studies from PubMed, Scopus, and Web of Science. The exclusion criteria comprised studies conducted only in vitro, not addressing infectious diseases, or not referencing the use of AI models as predictors. Data such as study type, year of publication, number of patients, study objective, ML algorithms used, features, and predictors were extracted from the included publications. All studies concluded that ML algorithms were useful to assist antimicrobial stewardship teams in multiple tasks such as identifying inappropriate prescribing practices, choosing the appropriate antibiotic therapy, or predicting AMR. The most extracted performance metric was AUC, which ranged from 0.64 to 0.992. Despite the risks and ethical concerns that AI raises, it can play a positive and promising role in ASP.<\/jats:p>","DOI":"10.3390\/antibiotics13040307","type":"journal-article","created":{"date-parts":[[2024,3,28]],"date-time":"2024-03-28T12:22:46Z","timestamp":1711628566000},"page":"307","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":52,"title":["Brave New World of Artificial Intelligence: Its Use in Antimicrobial Stewardship\u2014A Systematic Review"],"prefix":"10.3390","volume":"13","author":[{"given":"Rafaela","family":"Pinto-de-S\u00e1","sequence":"first","affiliation":[{"name":"Division of Microbiology, Department of Pathology, Faculty of Medicine, University of Porto, Alameda Prof. Hern\u00e2ni Monteiro, 4200-319 Porto, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1277-3401","authenticated-orcid":false,"given":"Bernardo","family":"Sousa-Pinto","sequence":"additional","affiliation":[{"name":"Department of Community Medicine, Information and Health Decision Sciences, Faculty of Medicine, University of Porto, 4200-319 Porto, Portugal"},{"name":"Center for Health Technology and Services Research\u2014CINTESIS@RISE, Faculty of Medicine, University of Porto, 4200-319 Porto, Portugal"}]},{"given":"Sofia","family":"Costa-de-Oliveira","sequence":"additional","affiliation":[{"name":"Division of Microbiology, Department of Pathology, Faculty of Medicine, University of Porto, Alameda Prof. Hern\u00e2ni Monteiro, 4200-319 Porto, Portugal"},{"name":"Center for Health Technology and Services Research\u2014CINTESIS@RISE, Faculty of Medicine, University of Porto, 4200-319 Porto, Portugal"}]}],"member":"1968","published-online":{"date-parts":[[2024,3,28]]},"reference":[{"key":"ref_1","unstructured":"(2023, September 20). 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