Cho K - Search Results

1

Approximating Intermediate Feature Maps of Self-Supervised Convolution Neural Network to Learn Hard Positive Representations in Chest Radiography.

Cho K, Kim KD, Jeong J, Nam Y, Kim J, Choi C, Lee S, Hong GS, Seo JB, Kim N. Cho K, et al. J Imaging Inform Med. 2024 Feb 21. doi: 10.1007/s10278-024-01032-x. Online ahead of print. J Imaging Inform Med. 2024. PMID: 38381382

2

An Open Medical Platform to Share Source Code and Various Pre-Trained Weights for Models to Use in Deep Learning Research.

Kim S, Cho S, Cho K, Seo J, Nam Y, Park J, Kim K, Kim D, Hwang J, Yun J, Jang M, Lee H, Kim N. Kim S, et al. Among authors: cho k, cho s. Korean J Radiol. 2021 Dec;22(12):2073-2081. doi: 10.3348/kjr.2021.0170. Epub 2021 Oct 26. Korean J Radiol. 2021. PMID: 34719891 Free PMC article. Review.

3

Bone suppression on pediatric chest radiographs via a deep learning-based cascade model.

Cho K, Seo J, Kyung S, Kim M, Hong GS, Kim N. Cho K, et al. Comput Methods Programs Biomed. 2022 Mar;215:106627. doi: 10.1016/j.cmpb.2022.106627. Epub 2022 Jan 10. Comput Methods Programs Biomed. 2022. PMID: 35032722

4

Enhancing deep learning based classifiers with inpainting anatomical side markers (L/R markers) for multi-center trials.

Kim KD, Cho K, Kim M, Lee KH, Lee S, Lee SM, Lee KH, Kim N. Kim KD, et al. Among authors: cho k. Comput Methods Programs Biomed. 2022 Jun;220:106705. doi: 10.1016/j.cmpb.2022.106705. Epub 2022 Feb 22. Comput Methods Programs Biomed. 2022. PMID: 35462346

5

Improved performance and robustness of multi-task representation learning with consistency loss between pretexts for intracranial hemorrhage identification in head CT.

Kyung S, Shin K, Jeong H, Kim KD, Park J, Cho K, Lee JH, Hong G, Kim N. Kyung S, et al. Among authors: cho k. Med Image Anal. 2022 Oct;81:102489. doi: 10.1016/j.media.2022.102489. Epub 2022 May 21. Med Image Anal. 2022. PMID: 35939912

6

CheSS: Chest X-Ray Pre-trained Model via Self-supervised Contrastive Learning.

Cho K, Kim KD, Nam Y, Jeong J, Kim J, Choi C, Lee S, Lee JS, Woo S, Hong GS, Seo JB, Kim N. Cho K, et al. J Digit Imaging. 2023 Jun;36(3):902-910. doi: 10.1007/s10278-023-00782-4. Epub 2023 Jan 26. J Digit Imaging. 2023. PMID: 36702988 Free PMC article.

7

MuSiC-ViT: A multi-task Siamese convolutional vision transformer for differentiating change from no-change in follow-up chest radiographs.

Cho K, Kim J, Kim KD, Park S, Kim J, Yun J, Ahn Y, Oh SY, Lee SM, Seo JB, Kim N. Cho K, et al. Med Image Anal. 2023 Oct;89:102894. doi: 10.1016/j.media.2023.102894. Epub 2023 Jul 12. Med Image Anal. 2023. PMID: 37562256

8

Overcoming the Challenges in the Development and Implementation of Artificial Intelligence in Radiology: A Comprehensive Review of Solutions Beyond Supervised Learning.

Hong GS, Jang M, Kyung S, Cho K, Jeong J, Lee GY, Shin K, Kim KD, Ryu SM, Seo JB, Lee SM, Kim N. Hong GS, et al. Among authors: cho k. Korean J Radiol. 2023 Nov;24(11):1061-1080. doi: 10.3348/kjr.2023.0393. Epub 2023 Aug 28. Korean J Radiol. 2023. PMID: 37724586 Free PMC article. Review.

9

Deep Learning for Automated Triaging of Stable Chest Radiographs in a Follow-up Setting.

Yun J, Ahn Y, Cho K, Oh SY, Lee SM, Kim N, Seo JB. Yun J, et al. Among authors: cho k. Radiology. 2023 Oct;309(1):e230606. doi: 10.1148/radiol.230606. Radiology. 2023. PMID: 37874243

10

Updated Primer on Generative Artificial Intelligence and Large Language Models in Medical Imaging for Medical Professionals.

Kim K, Cho K, Jang R, Kyung S, Lee S, Ham S, Choi E, Hong GS, Kim N. Kim K, et al. Among authors: cho k. Korean J Radiol. 2024 Mar;25(3):224-242. doi: 10.3348/kjr.2023.0818. Korean J Radiol. 2024. PMID: 38413108 Free PMC article. Review.

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