SORA

Advancing, promoting and sharing knowledge of health through excellence in teaching, clinical practice and research into the prevention and treatment of illness

Automated diabetic retinopathy image assessment softwares: large scale, real world evaluation of diagnostic accuracy and cost-effectiveness compared to human graders

Egan, CA; Rudnicka, A; Owen, C; Rudisill, C; Salas-Vega, S; Taylor, P; Liew, G; Lee, A; Bailey, C; Anderson, J; et al. Egan, CA; Rudnicka, A; Owen, C; Rudisill, C; Salas-Vega, S; Taylor, P; Liew, G; Lee, A; Bailey, C; Anderson, J; Tufail, A (2016) Automated diabetic retinopathy image assessment softwares: large scale, real world evaluation of diagnostic accuracy and cost-effectiveness compared to human graders. INVESTIGATIVE OPHTHALMOLOGY & VISUAL SCIENCE, 57 (12). ISSN 0146-0404
SGUL Authors: Rudnicka, Alicja Regina

[img]
Preview
PDF Published Version
Available under License Creative Commons Attribution Non-commercial No Derivatives.

Download (169kB) | Preview
Item Type: Article
Additional Information: ARVO 2016 Annual Meeting Abstracts These abstracts are licensed under a Creative Commons Attribution-NonCommercial-No Derivatives 4.0 International License. Go to http://iovs.arvojournals.org/ to access the versions of record.
Keywords: Ophthalmology & Optometry, 11 Medical And Health Sciences, 06 Biological Sciences
SGUL Research Institute / Research Centre: Academic Structure > Population Health Research Institute (INPH)
Journal or Publication Title: INVESTIGATIVE OPHTHALMOLOGY & VISUAL SCIENCE
ISSN: 0146-0404
Dates:
DateEvent
1 September 2016Published
Publisher License: Creative Commons: Attribution-Noncommercial-No Derivative Works 4.0
Projects:
Project IDFunderFunder ID
11/21/02National Institute for Health Researchhttp://dx.doi.org/10.13039/501100000272
Web of Science ID: WOS:000394210604082
URI: https://openaccess.sgul.ac.uk/id/eprint/108726

Actions (login required)

Edit Item Edit Item