Applying machine learning to consumer wearable data for the early detection of complications after pediatric appendectomy

Applying machine learning to consumer wearable data for the early detection of complications after pediatric appendectomy

Abstract When children are discharged from the hospital after surgery, their caregivers often rely on subjective assessments (e.g., appetite, fatigue) to monitor postoperative recovery as objective assessment tools are scarce at home. Such imprecise and one-dimensional evaluations can result in unwa...

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Bibliographic Details
Main Authors: Hassan M. K. Ghomrawi, Megan K. O’Brien, Michela Carter, Rebecca Macaluso, Rushmin Khazanchi, Michael Fanton, Christopher DeBoer, Samuel C. Linton, Suhail Zeineddin, J. Benjamin Pitt, Megan Bouchard, Angie Figueroa, Soyang Kwon, Jane L. Holl, Arun Jayaraman, Fizan Abdullah
Format: Article
Language:English
Published: Nature Portfolio 2023-08-01
Series:npj Digital Medicine
Online Access:https://doi.org/10.1038/s41746-023-00890-z

Internet

https://doi.org/10.1038/s41746-023-00890-z

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