Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Jeong-Hun Yoo"'
Autor:
Jeong-Hun Yoo, Han-Gyeol Yeom, WooSang Shin, Jong Pil Yun, Jong Hyun Lee, Seung Hyun Jeong, Hun Jun Lim, Jun Lee, Bong Chul Kim
Publikováno v:
Scientific Reports, Vol 11, Iss 1, Pp 1-9 (2021)
Abstract This paper proposes a convolutional neural network (CNN)-based deep learning model for predicting the difficulty of extracting a mandibular third molar using a panoramic radiographic image. The applied dataset includes a total of 1053 mandib
Externí odkaz:
https://doaj.org/article/ca8290bdccde45128660e9a4deb20ddd
Publikováno v:
Applied Sciences, Vol 11, Iss 10, p 4444 (2021)
Mandibular prognathism causes functional and esthetic problems. Therefore, many studies have been conducted to understand its etiology. Following our previous study, which revealed that the major characteristic of the mandible with prognathism is the
Externí odkaz:
https://doaj.org/article/22699adb8aa24462bba68dfb3f7d4c7e
Publikováno v:
Journal of Craniofacial Surgery; Jun2024, Vol. 35 Issue 4, p1138-1142, 5p
Autor:
Jun Lee, Bong Chul Kim, WooSang Shin, Seung Hyun Jeong, Han-Gyeol Yeom, Jong Hyun Lee, Jeong-Hun Yoo, Jong Pil Yun, Hun Jun Lim
Publikováno v:
Scientific Reports, Vol 11, Iss 1, Pp 1-9 (2021)
Scientific Reports
Scientific Reports
This paper proposes a convolutional neural network (CNN)-based deep learning model for predicting the difficulty of extracting a mandibular third molar using a panoramic radiographic image. The applied dataset includes a total of 1053 mandibular thir
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::277b698241693ac3d02e9af4e223c005
https://doaj.org/article/ca8290bdccde45128660e9a4deb20ddd
https://doaj.org/article/ca8290bdccde45128660e9a4deb20ddd