Youngyih Han on Muck Rack

Youngyih Han

South Korea
As seen in: PLOS ONE, MDPI
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Articles

Deep-learning-based segmentation using individual patient data on prostate cancer radiation therapy

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By Sangwoon Jeong, Wonjoong Cheon, Sungjin Kim, Youngyih Han
| PLOS ONE
Loading metrics Open Access Peer-reviewed Research Article Citation: Jeong S, Cheon W, Kim S, Park W, Han Y (2024) Deep-learning-based segmentation using individual patient data on prostate cancer radiation therapy. PLoS ONE 19(7): e0308181.
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The Prediction of Stress in Radiation Therapy: Integrating Artificial Intelligence with Biological Signals

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By Sangwoon Jeong, Hongryull Pyo, Youngyih Han
| MDPI
All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess.
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Prediction of Stress in Radiation Therapy: Integrating Artificial Intelligence with Biological Signals

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By Hongryull Pyo, Sangwoon Jeong, Youngyih Han
| preprints.org
Preprint Article Version 1 This version is not peer-reviewed Version 1 : Received: 11 January 2024 / Approved: 11 January 2024 / Online: 11 January 2024 (14:52:37 CET) Jeong, S.; Pyo, H.; Park, W.; Han, Y. Prediction of Stress in Radiation Therapy: Integrating Artificial Intelligence with Biological Signals. Preprints 2024, 2024010941. https://doi.org/10.20944/preprints202401.0941.v1 Jeong, S.; Pyo, H.; Park, W.; Han, Y.
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