Patient-level explainable machine learning to predict major adverse cardiovascular events from SPECT MPI and CCTA imaging

BACKGROUND: Machine learning (ML) has shown promise in improving the risk prediction in non-invasive cardiovascular imaging, including SPECT MPI and coronary CT angiography. However, most algorithms used remain black boxes to clinicians in how they compute their predictions. Furthermore, objective c...

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Detalles Bibliográficos
Autores principales: Alahdab, Fares, El Shawi, Radwa, Ahmed, Ahmed Ibrahim, Han, Yushui, Al-Mallah, Mouaz
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2023
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10651041/
https://www.ncbi.nlm.nih.gov/pubmed/37967112
http://dx.doi.org/10.1371/journal.pone.0291451

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10651041/
https://www.ncbi.nlm.nih.gov/pubmed/37967112
http://dx.doi.org/10.1371/journal.pone.0291451

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