Formal validation of a deep learning-based automated interpretation system for cardiac structure and function in adult echocardiography
The measurements of our DL interpretation had high accuracy, increased efficiency of the examination, and were inter-changeable with human experts' assessment. It has shown human-like patterns of measurements, as the same trend of difference can be observed between DL and different experienced readers.
Authors
- Shuyu Luo
- Xiaofang Zhong
- Wufeng Xue (ORCID: https://orcid.org/0000-0002-9776-0975)
- Qian Liu (ORCID: https://orcid.org/0000-0002-8705-5164)
- Yuanyuan Sheng (ORCID: https://orcid.org/0000-0002-9346-8475)
- Dong Ni (ORCID: https://orcid.org/0000-0002-9146-6003)
- Guijuan Peng
- Keming Tang
- Xiaohua Liu (ORCID: https://orcid.org/0000-0003-0427-2452)
- Xiaoxuan Lin (ORCID: https://orcid.org/0000-0002-4668-9101)
- Lixin Chen (ORCID: https://orcid.org/0000-0003-1679-7686)
- Yingqi Zheng
- Yumei Yang (ORCID: https://orcid.org/0000-0003-1647-6989)
- Jialan Zheng
- Rongbo Ling
- Jinfeng Xu (ORCID: https://orcid.org/0000-0002-0571-4155)
- Yingying Liu (ORCID: https://orcid.org/0000-0002-6792-8933)
Institutions
- Jinan University (CN)
- Shenzhen University (CN)
- Southern University of Science and Technology (CN)
Publication Details
- Journal
- Quantitative Imaging in Medicine and Surgery
- Published
- 2025-04-01
- DOI
- https://doi.org/10.21037/qims-24-1852
- Citations
- 1
- Primary Topic
- Cardiovascular Function and Risk Factors
- Type
- article
- Field-Weighted Citation Impact
- 1.39