A real-world demonstration of machine learning generalizability in the detection of intracranial hemorrhage on head computerized tomography

A real-world demonstration of machine learning generalizability in the detection of intracranial hemorrhage on head computerized tomography

Abstract Machine learning (ML) holds great promise in transforming healthcare. While published studies have shown the utility of ML models in interpreting medical imaging examinations, these are often evaluated under laboratory settings. The importance of real world evaluation is best illustrated by...

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Bibliographic Details
Main Authors: Hojjat Salehinejad, Jumpei Kitamura, Noah Ditkofsky, Amy Lin, Aditya Bharatha, Suradech Suthiphosuwan, Hui-Ming Lin, Jefferson R. Wilson, Muhammad Mamdani, Errol Colak
Format: Article
Language:English
Published: Nature Publishing Group 2021-08-01
Series:Scientific Reports
Online Access:https://doi.org/10.1038/s41598-021-95533-2

Internet

https://doi.org/10.1038/s41598-021-95533-2

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