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A machine learning algorithm for detecting abnormal patterns in continuous capnography and pulse oximetry monitoring

Published Online: 2024-04-15

Published Print: 2024-08

Authors

Spijkerboer, Feline L.

Overdyk, Frank J.

Dahan, Albert
Funding

Funding for this research was provided by:

Medtronic
License Information

Text and Data Mining valid from 2024-04-15

Version of Record valid from 2024-04-15
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Article History

Received: 10 November 2023

Accepted: 17 March 2024

First Online: 15 April 2024

Declarations

:

: FLS and AD or their institution received financial support from Medtronic in the form of consulting fees to support the current analysis. Further, AD or their institution received consulting fees from Medtronic for serving on the Clinical Events Committee of the original trial, which was sponsored by Medtronic. FJO declares that he has no competing interests.

: Ethics approval was collected for each site that participated in the original PRODIGY trial. All methods were carried out in accordance with relevant guidelines and regulations (Declaration of Helsinki).

: Written informed consent was required before a patient was enrolled in the original PRODIGY trial.

: Not applicable.

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