<div class="csl-bib-body">
<div class="csl-entry">Kapral, L., Dibiasi, C., Jeremic, N., Bartos, S., Behrens, S., Bilir, A., Heitzinger, C., & Kimberger, O. (2024). Development and external validation of temporal fusion transformer models for continuous intraoperative blood pressure forecasting. <i>EClinicalMedicine</i>, <i>75</i>, Article 102797. https://doi.org/10.1016/j.eclinm.2024.102797</div>
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dc.identifier.issn
2589-5370
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dc.identifier.uri
http://hdl.handle.net/20.500.12708/209321
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dc.description.abstract
During surgery, intraoperative hypotension is associated with postoperative morbidity and should therefore be avoided. Predicting the occurrence of hypotension in advance may allow timely interventions to prevent hypotension. Previous prediction models mostly use high-resolution waveform data, which is often not available.
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dc.language.iso
en
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dc.publisher
ELSEVIER
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dc.relation.ispartof
EClinicalMedicine
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dc.subject
Blood pressure forecasting
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dc.subject
Continuous prediction
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dc.subject
Haemodynamic monitoring
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dc.subject
Intraoperative hypotension
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dc.subject
Machine learning
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dc.subject
Temporal fusion transformer
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dc.title
Development and external validation of temporal fusion transformer models for continuous intraoperative blood pressure forecasting