Enhancing the diagnosis of functionally relevant coronary artery disease with 
machine learning

Bock, Christian; Walter, Joan Elias; Rieck, Bastian; Strebel, Ivo; Rumora, Klara; Schaefer, Ibrahim; Zellweger, Michael J.; Borgwardt, Karsten; Müller, Christian

doi:10.1038/s41467-024-49390-y

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Enhancing the diagnosis of functionally relevant coronary artery disease with machine learning

Bock, C., Walter, J. E., Rieck, B., Strebel, I., Rumora, K., Schaefer, I., et al. (2024). Enhancing the diagnosis of functionally relevant coronary artery disease with machine learning. Nature Communications, 15: 5034. doi:10.1038/s41467-024-49390-y.

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Item Permalink: https://hdl.handle.net/21.11116/0000-000F-733A-F Version Permalink: https://hdl.handle.net/21.11116/0000-000F-733B-E

Genre: Journal Article

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Creators:
Bock, Christian¹, Author
Walter, Joan Elias¹, Author
Rieck, Bastian¹, Author
Strebel, Ivo¹, Author
Rumora, Klara¹, Author
Schaefer, Ibrahim¹, Author
Zellweger, Michael J.¹, Author
Borgwardt, Karsten², Author
Müller, Christian¹, Author

Affiliations:
1External Organizations, ou_persistent22
2Borgwardt, Karsten / Machine Learning and Systems Biology, Max Planck Institute of Biochemistry, Max Planck Society, ou_3502542

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Dates: Published Online: 2024-06-12

Publication Status: Published online

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Rev. Type: Peer

Identifiers: DOI: 10.1038/s41467-024-49390-y

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Title: Nature Communications

Source Genre: Journal

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Pages: - Volume / Issue: 15 Sequence Number: 5034 Start / End Page: - Identifier: ISSN: 2041-1723