Learning to learn in medical applications: A journey through optimization

Azade Farshad, Yousef Yeganeh, Nassir Navab

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

4 Scopus citations

Abstract

Meta learning or learning to learn has been an attractive topic of research in the past years. Different methods in this area have been proposed to solve existing problems in the machine learning world. One of the common problems in machine learning that has received much attention in recent years is few-shot learning. Meta learning has been the natural solution to many few-shot learning problems. In this chapter, we introduce some background in meta learning. Then, we provide some examples of its applications in different areas, especially in medical imaging.

Original languageEnglish
Title of host publicationMeta Learning with Medical Imaging and Health Informatics Applications
PublisherElsevier
Pages3-25
Number of pages23
ISBN (Electronic)9780323998512
ISBN (Print)9780323998529
DOIs
StatePublished - 1 Jan 2022

Keywords

  • Few-shot learning
  • Medical imaging
  • Meta learning

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