Spatio-temporal hybrid neural networks reduce erroneous human “judgement calls” in the diagnosis of Takotsubo syndrome

BACKGROUND: We investigate whether deep learning (DL) neural networks can reduce erroneous human “judgment calls” on bedside echocardiograms and help distinguish Takotsubo syndrome (TTS) from anterior wall ST segment elevation myocardial infarction (STEMI). METHODS: We developed a single-channel (DC...

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Detalles Bibliográficos
Autores principales: Zaman, Fahim, Ponnapureddy, Rakesh, Wang, Yi Grace, Chang, Amanda, Cadaret, Linda M, Abdelhamid, Ahmed, Roy, Shubha D, Makan, Majesh, Zhou, Ruihai, Jayanna, Manju B, Gnall, Eric, Dai, Xuming, Singh, Avneet, Zheng, Jingsheng, Boppana, Venkata S, Wang, Feng, Singh, Pahul, Wu, Xiaodong, Liu, Kan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2021
Materias:
Research Paper
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8426197/
https://www.ncbi.nlm.nih.gov/pubmed/34522872
http://dx.doi.org/10.1016/j.eclinm.2021.101115

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8426197/
https://www.ncbi.nlm.nih.gov/pubmed/34522872
http://dx.doi.org/10.1016/j.eclinm.2021.101115

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