1 code implementation • 7 Jun 2019 • Tiarnan D. Keenan, Shazia Dharssi, Yifan Peng, Qingyu Chen, Elvira Agrón, Wai T. Wong, Zhiyong Lu, Emily Y. Chew
Results: The deep learning models (GA detection, CGA detection from all eyes, and centrality detection from GA eyes) had AUC of 0. 933-0. 976, 0. 939-0. 976, and 0. 827-0. 888, respectively.
no code implementations • 2 Dec 2018 • Qingyu Chen, Yifan Peng, Tiarnan Keenan, Shazia Dharssi, Elvira Agron, Wai T. Wong, Emily Y. Chew, Zhiyong Lu
Built on our previous work DeepSeeNet, we developed a novel deep learning model for automated classification of images into the 9-step scale.
Age-Related Macular Degeneration Classification Classification +2
1 code implementation • 19 Nov 2018 • Yifan Peng, Shazia Dharssi, Qingyu Chen, Tiarnan D. Keenan, Elvira Agrón, Wai T. Wong, Emily Y. Chew, Zhiyong Lu
DeepSeeNet simulates the human grading process by first detecting individual AMD risk factors (drusen size, pigmentary abnormalities) for each eye and then calculating a patient-based AMD severity score using the AREDS Simplified Severity Scale.