کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
4964925 | 1447938 | 2017 | 27 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Comparing humans and deep learning performance for grading AMD: A study in using universal deep features and transfer learning for automated AMD analysis
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
نرم افزارهای علوم کامپیوتر
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: Comparing humans and deep learning performance for grading AMD: A study in using universal deep features and transfer learning for automated AMD analysis Comparing humans and deep learning performance for grading AMD: A study in using universal deep features and transfer learning for automated AMD analysis](/preview/png/4964925.png)
چکیده انگلیسی
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.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computers in Biology and Medicine - Volume 82, 1 March 2017, Pages 80-86
Journal: Computers in Biology and Medicine - Volume 82, 1 March 2017, Pages 80-86
نویسندگان
Philippe Burlina, Katia D. Pacheco, Neil Joshi, David E. Freund, Neil M. Bressler,