default author photo

Denise Oro

Gubra

United States

SCHOLARLY PAPERS

1

DOWNLOADS

59

TOTAL CITATIONS

2

Scholarly Papers (1)

Actions:
Email selected abstracts
1.

Nuclear Morphology is a Deep Learning Biomarker of Senescence Across Tissues and Species

Number of pages: 49 Posted: 07 Apr 2021
Indra Heckenbach, Michael Ben Ezra, Garik V. Mkrtchyan, Jakob Sture Madsen, Malte Hasle Nielsen, Denise Oro, Laust H. Mortensen, Eric Verdin, Rudi G.J. Westendorp and Morten Scheibye-Knudsen
University of Copenhagen - Center for Healthy Aging, University of Copenhagen - Center for Healthy Aging, University of Copenhagen - Center for Healthy Aging, University of Copenhagen - Center for Healthy Aging, Gubra, Gubra, University of Copenhagen - Section of Epidemiology, Buck Institute for Research on Aging, University of Copenhagen - Section of Epidemiology and University of Copenhagen - Center for Healthy Aging
Downloads 59 (970,490)
Citation 2

Abstract:

Loading...

cellular senescence, aging, deep learning, cell morphology, image classification, DNA damage foci, progeria, dermal aging, cancer incidence, astrocytes