Development of a machine learning model using electrocardiogram signals to improve acute pulmonary embolism screening

AIMS: Clinical scoring systems for pulmonary embolism (PE) screening have low specificity and contribute to computed tomography pulmonary angiogram (CTPA) overuse. We assessed whether deep learning models using an existing and routinely collected data modality, electrocardiogram (ECG) waveforms, can...

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Detalles Bibliográficos
Autores principales: Somani, Sulaiman S, Honarvar, Hossein, Narula, Sukrit, Landi, Isotta, Lee, Shawn, Khachatoorian, Yeraz, Rehmani, Arsalan, Kim, Andrew, De Freitas, Jessica K, Teng, Shelly, Jaladanki, Suraj, Kumar, Arvind, Russak, Adam, Zhao, Shan P, Freeman, Robert, Levin, Matthew A, Nadkarni, Girish N, Kagen, Alexander C, Argulian, Edgar, Glicksberg, Benjamin S
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2021
Materias:
Original Articles
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8946569/
https://www.ncbi.nlm.nih.gov/pubmed/35355847
http://dx.doi.org/10.1093/ehjdh/ztab101

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8946569/
https://www.ncbi.nlm.nih.gov/pubmed/35355847
http://dx.doi.org/10.1093/ehjdh/ztab101

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