Artificial intelligence in sepsis early prediction and diagnosis using unstructured data in healthcare

Artificial intelligence in sepsis early prediction and diagnosis using unstructured data in healthcare

Early prediction and diagnosis of sepsis, which is critical in reducing mortality, is challenging as many of its signs and symptoms are similar to other less critical conditions. Here, the authors develop an artificial intelligence algorithm which uses both structured data and unstructured clinical...

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Bibliographic Details
Main Authors: Kim Huat Goh, Le Wang, Adrian Yong Kwang Yeow, Hermione Poh, Ke Li, Joannas Jie Lin Yeow, Gamaliel Yu Heng Tan
Format: Article
Language:English
Published: Nature Publishing Group 2021-01-01
Series:Nature Communications
Online Access:https://doi.org/10.1038/s41467-021-20910-4
Description
Summary:Early prediction and diagnosis of sepsis, which is critical in reducing mortality, is challenging as many of its signs and symptoms are similar to other less critical conditions. Here, the authors develop an artificial intelligence algorithm which uses both structured data and unstructured clinical notes to predict sepsis.
ISSN:2041-1723

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