{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,5,14]],"date-time":"2025-05-14T09:49:20Z","timestamp":1747216160811,"version":"3.40.5"},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"type":"print","value":"9781643684567"},{"type":"electronic","value":"9781643684574"}],"license":[{"start":{"date-parts":[[2024,1,25]],"date-time":"2024-01-25T00:00:00Z","timestamp":1706140800000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,1,25]]},"abstract":"<jats:p>Real-world performance of machine learning (ML) models is crucial for safely and effectively embedding them into clinical decision support (CDS) systems. We examined evidence about the performance of contemporary ML-based CDS in clinical settings. A systematic search of four bibliographic databases identified 32 studies over a 5-year period. The CDS task, ML type, ML method and real-world performance was extracted and analysed. Most ML-based CDS supported image recognition and interpretation (n=12; 38%) and risk assessment (n=9; 28%). The majority used supervised learning (n=28; 88%) to train random forests (n=7; 22%) and convolutional neural networks (n=7; 22%). Only 12 studies reported real-world performance using heterogenous metrics; and performance degraded in clinical settings compared to model validation. The reporting of model performance is fundamental to ensuring safe and effective use of ML-based CDS in clinical settings. There remain opportunities to improve reporting.<\/jats:p>","DOI":"10.3233\/shti230971","type":"book-chapter","created":{"date-parts":[[2024,1,25]],"date-time":"2024-01-25T10:20:04Z","timestamp":1706178004000},"source":"Crossref","is-referenced-by-count":0,"title":["How Well Do AI-Enabled Decision Support Systems Perform in Clinical Settings?"],"prefix":"10.3233","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5155-6904","authenticated-orcid":false,"given":"Anindya Pradipta","family":"Susanto","sequence":"first","affiliation":[{"name":"Australian Institute of Health Innovation, Macquarie University, Australia"},{"name":"Faculty of Medicine, Universitas Indonesia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"David","family":"Lyell","sequence":"additional","affiliation":[{"name":"Australian Institute of Health Innovation, Macquarie University, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bambang","family":"Widyantoro","sequence":"additional","affiliation":[{"name":"Faculty of Medicine, Universitas Indonesia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shlomo","family":"Berkovsky","sequence":"additional","affiliation":[{"name":"Australian Institute of Health Innovation, Macquarie University, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Farah","family":"Magrabi","sequence":"additional","affiliation":[{"name":"Australian Institute of Health Innovation, Macquarie University, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"7437","container-title":["Studies in Health Technology and Informatics","MEDINFO 2023 \u2014 The Future Is Accessible"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/SHTI230971","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,25]],"date-time":"2024-01-25T10:20:06Z","timestamp":1706178006000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/SHTI230971"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,1,25]]},"ISBN":["9781643684567","9781643684574"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/shti230971","relation":{},"ISSN":["0926-9630","1879-8365"],"issn-type":[{"type":"print","value":"0926-9630"},{"type":"electronic","value":"1879-8365"}],"subject":[],"published":{"date-parts":[[2024,1,25]]}}}