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Hae Ryoun Park

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Articles

Analysis of the Forces and Moments in Canine Bodily Movement with Different Clear Aligners’ Extraction Space Designs

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By Youn-Kyung Choi, Sung-Hun Kim, Hae Ryoun Park, Seong-Sik Kim
| 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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Gene signatures associated with barrier dysfunction and infection in oral lichen planus identified by analysis of transcriptomic data

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By Phúc Võ, Hae Ryoun Park, Ahreum Lee, Sung-Hee Jeong
| PLOS
Loading metrics Open Access Peer-reviewed Research Article Phuc Thi-Duy Vo, Sun Shim Choi, Hae Ryoun Park, Ahreum Lee, Sung-Hee Jeong , Youngnim Choi Phuc Thi-Duy Vo, Sun Shim Choi, Hae Ryoun Park, Ahreum Lee, Sung-Hee Jeong, Youngnim Choi Published: September 10, 2021 https://doi.org/10.1371/journal.pone.0257356 Figures Abstract Oral lichen planus (OLP) is one of the most prevalent oral mucosal diseases, but there is no cure for OLP yet.
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Automatic mandibular canal detection using a deep convolutional neural network

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By Gloria Kwak, Jae Joon Hwang, Eun-Jung Kwak, Hae Ryoun Park
| Nature Verified
Abstract The practicability of deep learning techniques has been demonstrated by their successful implementation in varied fields, including diagnostic imaging for clinicians. In accordance with the increasing demands in the healthcare industry, techniques for automatic prediction and detection are being widely researched. Particularly in dentistry, for various reasons, automated mandibular canal detection has become highly desirable.
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