Transfer learning for medical image classification: a literature review

🤖 Plain-English Summary

BACKGROUND: Transfer learning (TL) with convolutional neural networks aims to improve performances on a new task by leveraging the knowledge of similar tasks learned in advance. We encourage data scientists and practitioners to use deep models (e.g.

🔑 Key Findings

• It has made a major contribution to medical image analysis as it overcomes the data scarcity problem as well as it saves time and hardware resources.
• However, transfer learning has been arbitrarily configured in the majority of studies.
• This review paper attempts to provide guidance for selecting a model and TL approaches for the medical image classification task.

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