Qingyu Chen 0001, Tiarnan D. Keenan, Elvira Agrón, Amr S. Elsawy, Emily Y. Chew, Zhiyong Lu. Deep learning automated diagnosis and quantitative classification of cataract type and severity: quantifying the effectiveness and usability of deep learning-assisted disease diagnosis models with 14 ophthalmologists and multi-center validations. In AMIA 2022, American Medical Informatics Association Annual Symposium, Washington, DC, USA, November 5-9, 2022. AMIA, 2022. [doi]
@inproceedings{0001KAECL22,
title = {Deep learning automated diagnosis and quantitative classification of cataract type and severity: quantifying the effectiveness and usability of deep learning-assisted disease diagnosis models with 14 ophthalmologists and multi-center validations},
author = {Qingyu Chen 0001 and Tiarnan D. Keenan and Elvira Agrón and Amr S. Elsawy and Emily Y. Chew and Zhiyong Lu},
year = {2022},
url = {https://knowledge.amia.org/76677-amia-1.4637602/f007-1.4641746/f007-1.4641747/340-1.4642099/502-1.4642096},
researchr = {https://researchr.org/publication/0001KAECL22},
cites = {0},
citedby = {0},
booktitle = {AMIA 2022, American Medical Informatics Association Annual Symposium, Washington, DC, USA, November 5-9, 2022},
publisher = {AMIA},
}