Artificial intelligence-assisted echocardiographic monitoring in pediatric patients on extracorporeal membrane oxygenation
Automated EF measurements are feasible for pediatric ECMO echocardiography. AI-automated analysis of echocardiography for quantifying left ventricular function in critically ill children has good consistency and reproducibility with that of clinical experts. The automated echocardiographic EF method is reliable for the quantitative evaluation of different heart rates. It can fully support the course of ECMO treatment, and it can help improve the accuracy of quantitative evaluation.
Authors
- Xunyi Chen
- Weiling Chen (ORCID: https://orcid.org/0000-0002-1400-1659)
- Bei Xia
- Zijian Tang (ORCID: https://orcid.org/0000-0002-3063-3576)
- Zhifan Gao (ORCID: https://orcid.org/0000-0002-1576-4439)
- Heye Zhang (ORCID: https://orcid.org/0000-0003-3828-0629)
- Lin Zhou (ORCID: https://orcid.org/0000-0002-6428-7392)
- Jinhui Wu (ORCID: https://orcid.org/0000-0001-8809-1290)
- Shu-min Fan
- Yu Zhang (ORCID: https://orcid.org/0000-0003-1025-906X)
- Wei Yu (ORCID: https://orcid.org/0000-0002-4078-209X)
- Zhenxuan Zhang (ORCID: https://orcid.org/0009-0002-2904-2848)
Institutions
- Sun Yat-sen University (CN)
- Shenzhen Children's Hospital (CN)
Publication Details
- Journal
- Frontiers in Cardiovascular Medicine
- Published
- 2024-12-11
- DOI
- https://doi.org/10.3389/fcvm.2024.1418741
- Citations
- 4
- Primary Topic
- Mechanical Circulatory Support Devices
- Type
- article
- Field-Weighted Citation Impact
- 0.74