Age and Sex Estimation Using Artificial Intelligence From Standard 12-Lead ECGs

Sex and age have long been known to affect the ECG. Several biologic variables and anatomic factors may contribute to sex and age-related differences on the ECG. We hypothesized that a convolutional neural network (CNN) could be trained through a process called deep learning to predict a person’s ag...

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Dettagli Bibliografici
Pubblicato in:Circ Arrhythm Electrophysiol
Autori principali: Attia, Zachi I., Friedman, Paul A., Noseworthy, Peter A., Lopez-Jimenez, Francisco, Ladewig, Dorothy J., Satam, Gaurav, Pellikka, Patricia A., Munger, Thomas M., Asirvatham, Samuel J., Scott, Christopher G., Carter, Rickey E., Kapa, Suraj
Natura: Artigo
Lingua:Inglês
Pubblicazione: Lippincott Williams & Wilkins 2019
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Original Articles
Accesso online:https://ncbi.nlm.nih.gov/pmc/articles/PMC7661045/
https://ncbi.nlm.nih.gov/pubmed/31450977
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1161/CIRCEP.119.007284
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