<p>Using AI for Detecting Clinical Deterioration: Insights and Responses from the Care Team</p>

Lisa Shieh; Yejin Jeong; Margaret Smith; Robert Gallo; Jerri Westphal; Aubrey Florom-Smith; Lisa  Knowlton; Steven  Lin

doi:10.7490/f1000research.1120027.1

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Shieh L, Jeong Y, Smith M et al. Using AI for Detecting Clinical Deterioration: Insights and Responses from the Care Team [version 1; not peer reviewed]. F1000Research 2024, 13:1440 (poster) (https://doi.org/10.7490/f1000research.1120027.1)

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Using AI for Detecting Clinical Deterioration: Insights and Responses from the Care Team

Lisa Shieh¹, Yejin Jeong, Margaret Smith, Robert Gallo, Jerri Westphal, Aubrey Florom-Smith, Lisa Knowlton, Steven Lin

Published 28 Nov 2024 (https://doi.org/10.7490/f1000research.1120027.1)

Author Affiliations

¹ Medicine, Stanford University School of Medicine, Stanford, California, USA

Copyright © 2024 Shieh L et al. This is an open access work distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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CITE

Published 28 Nov 2024

Using AI for Detecting Clinical Deterioration: Insights and Responses from the Care Team
[version 1; not peer reviewed]

Lisa Shieh¹, Yejin Jeong, Margaret Smith, Robert Gallo, Jerri Westphal, Aubrey Florom-Smith, Lisa Knowlton, Steven Lin

Author Affiliations

¹ Medicine, Stanford University School of Medicine, Stanford, California, USA

Presented at

North American Primary Care Research Group Annual Meeting, 2024

Abstract

Competing Interests

No competing interests were disclosed

Keywords

AI clinical pathway, clinical deterioration, team engagement

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