📣 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.

ResNet-SCDA-50 for Breast Abnormality Classification. (2021)

First Author: Yu X

Attributed to: Driving innovation in precision medicine through translational life sciences research at the University of Leicester funded by UKRI

Abstract

No abstract provided

Bibliographic Information

Digital Object Identifier: http://dx.doi.org/10.1109/tcbb.2020.2986544

PubMed Identifier: 32287004

Publication URI: http://europepmc.org/abstract/MED/32287004

Type: Journal Article/Review

Volume: 18

Parent Publication: IEEE/ACM transactions on computational biology and bioinformatics

Issue: 1

ISSN: 1545-5963