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Development of a machine learning model to predict intensive care unit bed demand for adult elective surgical patients at a large United Kingdom National Health Service Trust.

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Title: Development of a machine learning model to predict intensive care unit bed demand for adult elective surgical patients at a large United Kingdom National Health Service Trust.
Authors: Hunter J; Institute of Health Informatics, University College London, London, UK., Vaidya H; Institute of Health Informatics, University College London, London, UK., Crowe S; Clinical Operational Research Unit, University College London, London, UK., Utley M; Clinical Operational Research Unit, University College London, London, UK., King Z; Clinical Operational Research Unit, University College London, London, UK., Li K; Institute of Health Informatics, University College London, London, UK., Harris S; University College London Hospitals, NHS Foundation Trust, London, UK.
Source: BJA open [BJA Open] 2026 Jan 16; Vol. 17, pp. 100513. Date of Electronic Publication: 2026 Jan 16 (Print Publication: 2026).
Publication Type: Journal Article
Journal Info: Publisher: Elsevier Ltd Country of Publication: England NLM ID: 9918419157906676 Publication Model: eCollection Cited Medium: Internet ISSN: 2772-6096 (Electronic) Linking ISSN: 27726096 NLM ISO Abbreviation: BJA Open Subsets: PubMed not MEDLINE
Database: MEDLINE Ultimate
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PubType: Academic Journal
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  Data: <searchLink fieldCode="AU" term="%22Hunter+J%22">Hunter J</searchLink>; Institute of Health Informatics, University College London, London, UK.<br /><searchLink fieldCode="AU" term="%22Vaidya+H%22">Vaidya H</searchLink>; Institute of Health Informatics, University College London, London, UK.<br /><searchLink fieldCode="AU" term="%22Crowe+S%22">Crowe S</searchLink>; Clinical Operational Research Unit, University College London, London, UK.<br /><searchLink fieldCode="AU" term="%22Utley+M%22">Utley M</searchLink>; Clinical Operational Research Unit, University College London, London, UK.<br /><searchLink fieldCode="AU" term="%22King+Z%22">King Z</searchLink>; Clinical Operational Research Unit, University College London, London, UK.<br /><searchLink fieldCode="AU" term="%22Li+K%22">Li K</searchLink>; Institute of Health Informatics, University College London, London, UK.<br /><searchLink fieldCode="AU" term="%22Harris+S%22">Harris S</searchLink>; University College London Hospitals, NHS Foundation Trust, London, UK.
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  Data: <searchLink fieldCode="JN" term="%229918419157906676%22">BJA open</searchLink> [BJA Open] 2026 Jan 16; Vol. 17, pp. 100513. <i>Date of Electronic Publication: </i>2026 Jan 16 (<i>Print Publication: </i>2026).
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  Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22Elsevier+Ltd%22">Elsevier Ltd </searchLink><i>Country of Publication: </i>England <i>NLM ID: </i>9918419157906676 <i>Publication Model: </i>eCollection <i>Cited Medium: </i>Internet <i>ISSN: </i>2772-6096 (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2227726096%22">27726096 </searchLink><i>NLM ISO Abbreviation: </i>BJA Open <i>Subsets: </i>PubMed not MEDLINE
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      – Type: doi
        Value: 10.1016/j.bjao.2025.100513
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      – Code: eng
        Text: English
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              Text: 2026 Jan 16
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