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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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| Foilsithe in: | Circ Arrhythm Electrophysiol |
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| Main Authors: | , , , , , , , , , , , |
| Formáid: | Artigo |
| Teanga: | Inglês |
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Lippincott Williams & Wilkins
2019
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| Ábhair: | |
| Rochtain Ar Líne: | 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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