📣 Help Shape the Future of UKRI's Gateway to Research (GtR)

We're improving UKRI's Gateway to Research and are seeking your input! If you would be interested in being interviewed about the improvements we're making and to have your say about how we can make GtR more user-friendly, impactful, and effective for the Research and Innovation community, please email gateway@ukri.org.

Predicting sex from retinal fundus photographs using automated deep learning. (2021)

First Author: Korot E

Abstract

No abstract provided

Bibliographic Information

Digital Object Identifier: http://dx.doi.org/10.1038/s41598-021-89743-x

PubMed Identifier: 33986429

Publication URI: http://europepmc.org/abstract/MED/33986429

Type: Journal Article/Review

Volume: 11

Parent Publication: Scientific reports

Issue: 1

ISSN: 2045-2322