Advances in the application of deep learning to the risk assessment of nerve damage associated with extraction of impacted mandibular third molars

The application of deep learning (DL) has become widespread with the development of digital medicine. At present, DL has been gradually applied to the fields of stomatology. Multiple studies have applied DL, combined with preoperative examination images such as X ray and cone beam CT (CBCT) images,...

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Main Authors: HUANG Jiaqi, LI Ang, KOU Yifan, Ayagusi Sailike, CHEN Lidan, ZHANG Xueming
Format: Article
Language:zho
Published: Editorial Office of Journal of Oral and Maxillofacial Surgery 2024-06-01
Series:Kouqiang hemian waike zazhi
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Online Access:https://journal06.magtech.org.cn/Jweb_joms/EN/10.12439/kqhm.1005-4979.2024.03.009
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author HUANG Jiaqi
LI Ang
KOU Yifan
Ayagusi Sailike
CHEN Lidan
ZHANG Xueming
author_facet HUANG Jiaqi
LI Ang
KOU Yifan
Ayagusi Sailike
CHEN Lidan
ZHANG Xueming
author_sort HUANG Jiaqi
collection DOAJ
description The application of deep learning (DL) has become widespread with the development of digital medicine. At present, DL has been gradually applied to the fields of stomatology. Multiple studies have applied DL, combined with preoperative examination images such as X ray and cone beam CT (CBCT) images, to assist clinical diagnosis and decision-making in dealing with impacted mandibular third molar (IMTM). Besides, inferior alveolar nerve (IAN) injury is one of the most serious sequelae after extraction of IMTM. Combined with imageological examination, DL can provide objective and accurate estimation of the risk of IAN injury to improve the outcome of treatment. This paper reviews the current application of DL in preoperative image recognition, preoperative auxiliary diagnosis and evaluation, and IAN injury prognosis prediction in the extraction of IMTM, and looked into the role of DL in the extraction of IMTM in the future.
format Article
id doaj-art-c8ebaee05d634d29ad8cfb41a14973cb
institution Kabale University
issn 1005-4979
language zho
publishDate 2024-06-01
publisher Editorial Office of Journal of Oral and Maxillofacial Surgery
record_format Article
series Kouqiang hemian waike zazhi
spelling doaj-art-c8ebaee05d634d29ad8cfb41a14973cb2025-08-25T06:11:05ZzhoEditorial Office of Journal of Oral and Maxillofacial SurgeryKouqiang hemian waike zazhi1005-49792024-06-0134322322610.12439/kqhm.1005-4979.2024.03.009Advances in the application of deep learning to the risk assessment of nerve damage associated with extraction of impacted mandibular third molarsHUANG Jiaqi0LI Ang1KOU Yifan2Ayagusi Sailike3CHEN Lidan4ZHANG Xueming5Shanghai Engineering Research Center of Tooth Restoration and Regeneration & Tongji Research Institute of Stomatology & Department of Oral and Maxillofacial Surgery, Stomatological Hospital and Dental School, Tongji University, Shanghai 200072Shanghai Engineering Research Center of Tooth Restoration and Regeneration & Tongji Research Institute of Stomatology & Department of Oral and Maxillofacial Surgery, Stomatological Hospital and Dental School, Tongji University, Shanghai 200072School of Medicine, Tongji University, Shanghai 200092, ChinaShanghai Engineering Research Center of Tooth Restoration and Regeneration & Tongji Research Institute of Stomatology & Department of Oral and Maxillofacial Surgery, Stomatological Hospital and Dental School, Tongji University, Shanghai 200072Shanghai Engineering Research Center of Tooth Restoration and Regeneration & Tongji Research Institute of Stomatology & Department of Oral and Maxillofacial Surgery, Stomatological Hospital and Dental School, Tongji University, Shanghai 200072Shanghai Engineering Research Center of Tooth Restoration and Regeneration & Tongji Research Institute of Stomatology & Department of Oral and Maxillofacial Surgery, Stomatological Hospital and Dental School, Tongji University, Shanghai 200072The application of deep learning (DL) has become widespread with the development of digital medicine. At present, DL has been gradually applied to the fields of stomatology. Multiple studies have applied DL, combined with preoperative examination images such as X ray and cone beam CT (CBCT) images, to assist clinical diagnosis and decision-making in dealing with impacted mandibular third molar (IMTM). Besides, inferior alveolar nerve (IAN) injury is one of the most serious sequelae after extraction of IMTM. Combined with imageological examination, DL can provide objective and accurate estimation of the risk of IAN injury to improve the outcome of treatment. This paper reviews the current application of DL in preoperative image recognition, preoperative auxiliary diagnosis and evaluation, and IAN injury prognosis prediction in the extraction of IMTM, and looked into the role of DL in the extraction of IMTM in the future.https://journal06.magtech.org.cn/Jweb_joms/EN/10.12439/kqhm.1005-4979.2024.03.009deep learningimpacted mandibular third molartooth extractionorthopantomogramcone beam ctinferior alveolar nerve injury
spellingShingle HUANG Jiaqi
LI Ang
KOU Yifan
Ayagusi Sailike
CHEN Lidan
ZHANG Xueming
Advances in the application of deep learning to the risk assessment of nerve damage associated with extraction of impacted mandibular third molars
Kouqiang hemian waike zazhi
deep learning
impacted mandibular third molar
tooth extraction
orthopantomogram
cone beam ct
inferior alveolar nerve injury
title Advances in the application of deep learning to the risk assessment of nerve damage associated with extraction of impacted mandibular third molars
title_full Advances in the application of deep learning to the risk assessment of nerve damage associated with extraction of impacted mandibular third molars
title_fullStr Advances in the application of deep learning to the risk assessment of nerve damage associated with extraction of impacted mandibular third molars
title_full_unstemmed Advances in the application of deep learning to the risk assessment of nerve damage associated with extraction of impacted mandibular third molars
title_short Advances in the application of deep learning to the risk assessment of nerve damage associated with extraction of impacted mandibular third molars
title_sort advances in the application of deep learning to the risk assessment of nerve damage associated with extraction of impacted mandibular third molars
topic deep learning
impacted mandibular third molar
tooth extraction
orthopantomogram
cone beam ct
inferior alveolar nerve injury
url https://journal06.magtech.org.cn/Jweb_joms/EN/10.12439/kqhm.1005-4979.2024.03.009
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AT chenlidan advancesintheapplicationofdeeplearningtotheriskassessmentofnervedamageassociatedwithextractionofimpactedmandibularthirdmolars
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