의료 인공지능 관련 survey paper 모음

오늘은 실질적으로 일하는데 도움이 될만한, 그러면서도 기초지식을 쌓기 좋은, CNN부터 시작해서 의료인공지능이 어떤 방향으로 흘러가고 있는지 트렌드를 볼수 있는 논문들을 좀 모아보았다.

(요즘 핫한 LLM쪽은 따로 정리해서 보기위해서 제외시켰다)

 

1. Medical Image Segmentation Review: The Success of U-Net (2022)

https://arxiv.org/pdf/2211.14830

 

2. Transformers in medical imaging: A survey

https://doi.org/10.1016/j.media.2023.102802

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3. nnU-Net Revisited: A Call for Rigorous Validation in 3D Medical Image Segmentation

https://arxiv.org/pdf/2404.09556

 

4. Embracing imperfect datasets: A review of deep learning solutions for medical image segmentation

https://doi.org/10.1016/j.media.2020.101693

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5. Loss odyssey in medical image segmentation

https://doi.org/10.1016/j.media.2021.102035

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6. A comprehensive survey on deep active learning in medical image analysis

https://doi.org/10.1016/j.media.2024.103201

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7. Deep Long-Tailed Learning: A Survey

https://arxiv.org/pdf/2110.04596