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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Autores principales: Hojjat Salehinejad, Jumpei Kitamura, Noah Ditkofsky, Amy Lin, Aditya Bharatha, Suradech Suthiphosuwan, Hui-Ming Lin, Jefferson R. Wilson, Muhammad Mamdani, Errol Colak
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2021
Materias:
Medicine
R
Science
Q
Acceso en línea:https://doaj.org/article/0a90015727c949899ea11517db07fa81
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