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http://hdl.handle.net/11054/2558
Title: | Towards a unified rheumatic heart disease imaging dataset. |
Author: | Howson, S. Evans, S. Booth, A. Stretton, B. Nelson, A. Kovoor, J. Kovoor, P. Gupta, A. Bacchi, S. |
Issue Date: | 2024 |
Publication Title: | Heart, Lung and Circulation |
Volume: | 33 |
Start Page: | e8 |
End Page: | e9 |
Abstract: | Artificial intelligence (AI) has the potential to improve access to services for underserved populations. Rheumatic heart disease (RHD) is set to be a condition that may benefit significantly from the innovations made possible through AI research [ [1] ]. As with essentially all AI research, developing an AI model for RHD detection will be contingent upon the presence of robust datasets. A unified and collaborative approach to the consolidation of RHD imaging datasets may expedite the development of these algorithms and enable higher algorithmic performance. |
URI: | http://hdl.handle.net/11054/2558 |
DOI: | https://doi.org/10.1016/j.hlc.2023.10.022 |
Internal ID Number: | 02541 |
Health Subject: | ARTIFICIAL INTELLIGENCE RHEUMATIC HEART DISEASE RURAL AND REMOTE |
Type: | Journal Article Article |
Appears in Collections: | Research Output |
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