Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4964925 | Computers in Biology and Medicine | 2017 | 27 Pages |
Abstract
This study demonstrates the efficacy of machine grading based on deep universal features/transfer learning when applied to ARIA and is a promising step in providing a pre-screener to identify individuals with intermediate AMD and also as a tool that can facilitate identifying such individuals for clinical studies aimed at developing improved therapies. It also demonstrates comparable performance between computer and physician grading.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science Applications
Authors
Philippe Burlina, Katia D. Pacheco, Neil Joshi, David E. Freund, Neil M. Bressler,