PhotoAgeClock: deep learning algorithms for development of non-invasive visual biomarkers of aging-Reference-Cited by-同舟云学术

PhotoAgeClock: deep learning algorithms for development of non-invasive visual biomarkers of aging

Published:2018-11-09 Issue:11 Volume:10 Page:3249-3259
ISSN:1945-4589
Container-title:Aging
language:en
Short-container-title:Aging

Author:

Bobrov Eugene¹²,Georgievskaya Anastasia¹³,Kiselev Konstantin¹,Sevastopolsky Artem¹⁴,Zhavoronkov Alex⁵⁶⁷,Gurov Sergey²,Rudakov Konstantin³,del Pilar Bonilla Tobar Maria⁸,Jaspers Sören⁸,Clemann Sven⁸

Affiliation:

1. HautAI OU, Tallinn, Estonia

2. Lomonosov Moscow State University, Moscow, Russia

3. Federal Research Center “Computer Science and Control” of the Russian Academy of Sciences, Moscow, Russia

4. Skolkovo Institute of Science and Technology, Moscow, Russia

5. Insilico Medicine, Rockville, MD 20850, USA

6. The Buck Institute for Research on Aging, Novato, CA 94945, USA

7. The Biogerontology Research Foundation, London, UK

8. Beiersdorf AG, Hamburg, Germany

Publisher

Impact Journals, LLC

Subject

Cell Biology,Ageing

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