Repository logo

Infoscience

  • English
  • French
Log In
Logo EPFL, École polytechnique fédérale de Lausanne

Infoscience

  • English
  • French
Log In
  1. Home
  2. Academic and Research Output
  3. Journal articles
  4. Multi-task learning for medical foundation models
 
research article

Multi-task learning for medical foundation models

Yang, Jiancheng  
July 19, 2024
Nature Computational Science

To address the challenge of pretraining foundational models with large datasets, a multi-task approach is proposed, thus helping to overcome the data scarcity problem in biomedical imaging.

  • Details
  • Metrics
Type
research article
DOI
10.1038/s43588-024-00658-9
Web of Science ID

WOS:001272277700003

PubMed ID

39030385

Author(s)
Yang, Jiancheng  

École Polytechnique Fédérale de Lausanne

Date Issued

2024-07-19

Publisher

SPRINGERNATURE

Published in
Nature Computational Science
Volume

4

Issue

7

Start page

473

End page

474

Subjects

Science & Technology

•

Technology

Editorial or Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
CVLAB  
Available on Infoscience
January 30, 2025
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/245959
Logo EPFL, École polytechnique fédérale de Lausanne
  • Contact
  • infoscience@epfl.ch

  • Follow us on Facebook
  • Follow us on Instagram
  • Follow us on LinkedIn
  • Follow us on X
  • Follow us on Youtube
AccessibilityLegal noticePrivacy policyCookie settingsEnd User AgreementGet helpFeedback

Infoscience is a service managed and provided by the Library and IT Services of EPFL. © EPFL, tous droits réservés