Diagnostic suspicion bias and machine learning: Breaking the awareness deadlock for sepsis detection.

Diagnostic suspicion bias and machine learning: Breaking the awareness deadlock for sepsis detection.

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Many early warning algorithms are downstream of clinical evaluation and diagnostic testing, which means that they may not be useful when clinicians fail to suspect illness and fail to order appropriate tests. Depending on how such algorithms handle missing data, they could even indicate "low ri...

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Bibliographic Details
Main Authors: Varesh Prasad, Baturay Aydemir, Iain E Kehoe, Chaya Kotturesh, Abigail O'Connell, Brett Biebelberg, Yang Wang, James C Lynch, Jeremy A Pepino, Michael R Filbin, Thomas Heldt, Andrew T Reisner
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2023-11-01
Series:PLOS Digital Health
Online Access:https://journals.plos.org/digitalhealth/article/file?id=10.1371/journal.pdig.0000365&type=printable

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https://journals.plos.org/digitalhealth/article/file?id=10.1371/journal.pdig.0000365&type=printable

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