Artificial intelligence-enabled fully automated detection of cardiac amyloidosis using electrocardiograms and echocardiograms
Cardiac amyloidosis is difficult to identify, given low prevalence and similarity of the symptoms to more prevalent disorders. Here the authors present a multi-modality, artificial intelligence-enabled pipeline, that enables automated detection of cardiac amyloidosis from inexpensive and accessible...
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| Autores principales: | , , , , , , , , , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Nature Portfolio
2021
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/0dd314b5edb84808bd06d6589d77bb90 |
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| Sumario: | Cardiac amyloidosis is difficult to identify, given low prevalence and similarity of the symptoms to more prevalent disorders. Here the authors present a multi-modality, artificial intelligence-enabled pipeline, that enables automated detection of cardiac amyloidosis from inexpensive and accessible measures. |
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