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Development and validation of open-source deep neural networks for comprehensive chest x-ray reading: a retrospective, multicentre study

Authors :
Cid, Yashin Dicente
Macpherson, Matthew
Gervais-Andre, Louise
Zhu, Yuanyi
Franco, Giuseppe
Santeramo, Ruggiero
Lim, Chee
Selby, Ian
Muthuswamy, Keerthini
Amlani, Ashik
Hopewell, Heath
Indrajeet, Das
Liakata, Maria
Hutchinson, Charles E
Goh, Vicky
Montana, Giovanni
Source :
The Lancet Digital Health; January 2024, Vol. 6 Issue: 1 pe44-e57, 14p
Publication Year :
2024

Abstract

Artificial intelligence (AI) systems for automated chest x-ray interpretation hold promise for standardising reporting and reducing delays in health systems with shortages of trained radiologists. Yet, there are few freely accessible AI systems trained on large datasets for practitioners to use with their own data with a view to accelerating clinical deployment of AI systems in radiology. We aimed to contribute an AI system for comprehensive chest x-ray abnormality detection.

Details

Language :
English
ISSN :
25897500
Volume :
6
Issue :
1
Database :
Supplemental Index
Journal :
The Lancet Digital Health
Publication Type :
Periodical
Accession number :
ejs64834442
Full Text :
https://doi.org/10.1016/S2589-7500(23)00218-2