切换至 "中华医学电子期刊资源库"

中华口腔医学研究杂志(电子版) ›› 2024, Vol. 18 ›› Issue (01) : 65 -69. doi: 10.3877/cma.j.issn.1674-1366.2024.01.011

综述

人工智能在口腔修复诊疗中的应用与进展
戴雨霖, 张新春()   
  1. 中山大学附属口腔医院,光华口腔医学院,广东省口腔医学重点实验室,广东省口腔疾病临床医学研究中心,广州 510055
  • 收稿日期:2023-06-08 出版日期:2024-02-01
  • 通信作者: 张新春

Artificial intelligence for prosthodontic treatments: Applications and development

Yulin Dai, Xinchun Zhang()   

  1. Hospital of Stomatology, Guanghua School of Stomatology, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Stomatology, Guangdong Provincial Clinical Research Center of Oral Diseases, Guangzhou 510055, China
  • Received:2023-06-08 Published:2024-02-01
  • Corresponding author: Xinchun Zhang
  • Supported by:
    Natural Science Foundation of Guangdong Province(2022A1515012485)
引用本文:

戴雨霖, 张新春. 人工智能在口腔修复诊疗中的应用与进展[J/OL]. 中华口腔医学研究杂志(电子版), 2024, 18(01): 65-69.

Yulin Dai, Xinchun Zhang. Artificial intelligence for prosthodontic treatments: Applications and development[J/OL]. Chinese Journal of Stomatological Research(Electronic Edition), 2024, 18(01): 65-69.

数字化与信息技术是21世纪以来口腔医学的主旋律,尤其在口腔修复医学中,人工智能(AI)技术的应用可促进其从初诊断到治疗完成后随访全流程的智能化升级。本文介绍了目前AI技术的概念,探讨其在口腔修复医学的应用与进展,以及现阶段存在的不足与未来发展方向,以期为临床医生与科研人员进一步将口腔医学与人工智能深入融合提供参考。

Digitalization and information technology have been the main theme of Oral Medicine since the 21st century. In particular, the application of artificial intelligence technology in Prosthodontics can promote the intelligent upgrading of the entire process from the initial diagnosis to the follow-ups after treatment. This article introduced the concept of the current artificial intelligence technologies, discussed the application and progress of artificial intelligence in Prosthodontics, as well as the existing deficiencies at the current stage and the future development directions, so as to provide references for clinical dentists and scientific researchers to further integrate Oral Medicine with artificial intelligence.

表1 用于口腔修复诊疗的人工智能技术的相关概念
[1]
胡敏.口腔医学领域人工智能及相关技术的研究和应用进展[J].中华口腔医学杂志202358(6):505-513. DOI:10.3760/cma.j.cn112144-20230505-00183.
[2]
刘洪臣,张戎.人工智能在口腔医学中的应用进展[J].中华医学信息导报202035(18):12. DOI:10.3760/cma.j.issn.1000-8039.2020.18.114.
[3]
Lee SJChung DAsano A,et al. Diagnosis of tooth prognosis using artificial intelligence[J]. Diagnostics(Basel)202212(6):1422. DOI:10.3390/diagnostics12061422.
[4]
Mayta-Tovalino FMunive-Degregori ALuza S,et al. Applications and perspectives of artificial intelligence,machine learning and "dentronics" in dentistry:A literature review[J]. J Int Soc Prev Community Dent202313(1):1-8. DOI:10.4103/jispcd.JISPCD_35_22.
[5]
Mohammad-Rahimi HMotamedian SRRohban MH,et al. Deep learning for caries detection:A systematic review[J]. J Dent2022122:104115. DOI:10.1016/j.jdent.2022.104115.
[6]
Yamaguchi SLee CKaraer O,et al. Predicting the debonding of CAD/CAM composite resin crowns with AI[J]. J Dent Res201998(11):1234-1238. DOI:10.1177/0022034519867641.
[7]
Pethani FDunn AG. Natural language processing for clinical notes in dentistry:A systematic review[J]. J Biomed Inform2023138:104282. DOI:10.1016/j.jbi.2023.104282.
[8]
林慧平,徐婷,林军.人工智能在口腔癌和口腔潜在恶性疾病诊断中的研究进展[J].国际口腔医学杂志202350(2):138-145. DOI:10.7518/gjkq.2023019.
[9]
Thurzo AUrbanová WNovák B,et al. Where is the artificial intelligence applied in dentistry?Systematic review and literature analysis[J]. Healthcare(Basel)202210(7):1269. DOI:10.3390/healthcare10071269.
[10]
Sarode SCSharma NKSarode G. A critical appraisal on cancer prognosis and artificial intelligence[J]. Future Oncol202218(13):1531-1534. DOI:10.2217/fon-2021-1528.
[11]
Hegde SAjila VZhu W,et al. Artificial intelligence in early diagnosis and prevention of oral cancer[J]. Asia Pac J Oncol Nurs20229(12):100133. DOI:10.1016/j.apjon.2022.100133.
[12]
Patil SAlbogami SHosmani J,et al. Artificial Intelligence in the diagnosis of oral diseases:Applications and pitfalls[J]. Diagnostics(Basel)202212(5):1029. DOI:10.3390/diagnostics12051029.
[13]
Li SLiu JZhou Z,et al. Artificial intelligence for caries and periapical periodontitis detection[J]. J Dent2022122:104107. DOI:10.1016/j.jdent.2022.104107.
[14]
Aliaga IJVera Vde Paz JF,et al. Modelling the longevity of dental restorations by means of a CBR system[J]. Biomed Res Int2015:540306. DOI:10.1155/2015/540306.
[15]
曾维,周善洛,郭际香,等.基于深度学习的口腔颌面部CT图像金属伪影消除与临床验证[J].中华口腔医学杂志202358(6):540-546. DOI:10.3760/cma.j.cn112144-20230302-00067.
[16]
Patcas RBornstein MSchätzle M,et al. Artificial intelligence in medico-dental diagnostics of the face:A narrative review of opportunities and challenges[J]. Clin Oral Investig202226(12):6871-6879. DOI:10.1007/s00784-022-04724-2.
[17]
Schneider LArsiwala-Scheppach LKrois J,et al. Benchmarking deep learning models for tooth structure segmentation[J]. J Dent Res2022101(11):1343-1349. DOI:10.1177/00220345221100169.
[18]
Alsomali MAlghamdi SAlotaibi S,et al. Development of a deep learning model for automatic localization of radiographic markers of proposed dental implant site locations[J]. Saudi Dent J202234(3):220-225. DOI:10.1016/j.sdentj.2022.01.002.
[19]
Wei JPeng MLi Q,et al. Evaluation of a Novel computer color matching system based on the improved back-propagation neural network model[J]. J Prosthodont201827(8):775-783. DOI:10.1111/jopr.12561.
[20]
Tian SWang MDai N,et al. DCPR-GAN:Dental crown prosthesis restoration using two-stage generative adversarial networks[J]. IEEE J Biomed Health Inform202126(1):151-160. DOI:10.1109/JBHI.2021.3119394.
[21]
Ding HCui ZMaghami E,et al. Morphology and mechanical performance of dental crown designed by 3D-DCGAN[J]. Dent Mater202339(3):320-332. DOI:10.1016/j.dental.2023.02.001.
[22]
Zhang JXia JLi J,et al. Reconstruction-based digital dental occlusion of the partially edentulous dentition[J]. IEEE J Biomed Health Inform201721(1):201-210. DOI:10.1109/JBHI.2015.2500191.
[23]
Chen QLin SWu J,et al. Automatic drawing of customized removable partial denture diagrams based on textual design for the clinical decision support system[J]. J Oral Sci202062(2):236-238. DOI:10.2334/josnusd.19-0138.
[24]
Takahashi TNozaki KGonda T,et al. A system for designing removable partial dentures using artificial intelligence. Part 1. Classification of partially edentulous arches using a convolutional neural network[J]. J Prosthodont Res202165(1):115-118. DOI:10.2186/jpr.JPOR_2019_354.
[25]
Yuan FCheng CDai N,et al. Prediction of aesthetic reconstruction effects in edentulous patients[J]. Sci Rep20177(1):18077. DOI:10.1038/s41598-017-17065-y.
[26]
Kurt Bayrakdar SOrhan KBayrakdar IS,et al. A deep learning approach for dental implant planning in cone-beam computed tomography images[J]. BMC Med Imaging202121(1):86. DOI:10.1186/s12880-021-00618-z.
[27]
Mangano FGAdmakin OLerner H,et al. Artificial intelligence and augmented reality for guided implant surgery planning:A proof of concept[J]. J Dent2023133:104485. DOI:10.1016/j.jdent.2023.104485.
[28]
Revilla-León MGómez-Polo MVyas S,et al. Artificial intelligence applications in implant dentistry:A systematic review[J]. J Prosthet Dent2023129(2):293-300. DOI:10.1016/j.prosdent.2021.05.008.
[29]
Sakai TLi HShimada T,et al. Development of artificial intelligence model for supporting implant drilling protocol decision making[J]. J Prosthodont Res202367(3):360-365. DOI:10.2186/jpr.JPR_D_22_00053.
[30]
周勇,张思慧,赵晓娴,等.口腔种植治疗培训中虚拟现实技术的应用及评价[J].中华口腔医学杂志202156(8):799-804. DOI:10.3760/cma.j.cn112144-20201210-00608.
[31]
刘琳,李鸿波,刘洪臣.混合现实技术在口腔医学中的应用展望[J].口腔颌面修复学杂志201920(2):102-107. DOI:10.19748/j.cn.kqxf.1009-3761.2019.02.009.
[32]
Ochandiano SGarcía-Mato DGonzalez-Alvarez A,et al. Computer-assisted dental implant placement following free flap reconstruction:Virtual planning,CAD/CAM templates,dynamic navigation and augmented reality[J]. Front Oncol202211:754943. DOI:10.3389/fonc.2021.754943.
[33]
Matin IHadzistevic MVukelic D,et al. Development of an expert system for the simulation model for casting metal substructure of a metal-ceramic crown design[J]. Comput Methods Programs Biomed2017146:27-35. DOI:10.1016/j.cmpb.2017.05.004.
[34]
Li HSakai TTanaka A,et al. Interpretable AI explores effective components of CAD/CAM resin composites[J]. J Dent Res2022101(11):1363-1371. DOI:10.1177/00220345221089251.
[35]
Mahmood MAVisan AIRistoscu C,et al. Artificial neural network algorithms for 3D printing[J]. Materials(Basel)202014(1):163. DOI:10.3390/ma14010163.
[36]
Kim RAbisado MVillaverde J,et al. A survey of image-based fault monitoring in additive manufacturing:Recent developments and future directions[J]. Sensors(Basel)202323(15):6821. DOI:10.3390/s23156821.
[37]
Qiao SCWu XYShi JY,et al. Accuracy and safety of a haptic operated and machine vision controlled collaborative robot for dental implant placement:A translational study[J]. Clin Oral Implants Res202334(8):839-849. DOI:10.1111/clr.14112.
[38]
Yang SChen JLi A,et al. Accuracy of autonomous robotic surgery for single-tooth implant placement:A case series[J]. J Dent2023132:104451. DOI:10.1016/j.jdent.2023.104451.
[39]
Chen JZhuang MTao B,et al. Accuracy of immediate dental implant placement with task-autonomous robotic system and navigation system:An in vitro study[J]. Clin Oral Implants Res2023. DOI:10.1111/clr.14104.
[40]
白石柱,任楠,冯志宏,等.自主式口腔种植机器人手术系统动物体内种植精度的研究[J].中华口腔医学杂志202156(2):170-174. DOI:10.3760/cma.j.cn112144-20210107-00008.
[41]
Bolding SReebye U. Accuracy of haptic robotic guidance of dental implant surgery for completely edentulous arches[J]. J Prosthet Dent2022128(4):639-647. DOI:10.1016/j.prosdent.2020.12.048.
[42]
Li CWang MDeng H,et al. Autonomous robotic surgery for zygomatic implant placement and immediately loaded implant-supported full-arch prosthesis:A preliminary research[J]. Int J Implant Dent20239(1):12. DOI:10.1186/s40729-023-00474-2.
[43]
Wang JShen YYang S. A practical marker-less image registration method for augmented reality oral and maxillofacial surgery[J]. Int J Comput Assist Radiol Surg201914(5):763-773. DOI:10.1007/s11548-019-01921-5.
[44]
李忠义,白鹤飞,王勇,等.牙体预备定量引导技术的研究现状[J].中华口腔医学杂志201853(2):137-140. DOI:10.3760/cma.j.issn.1002-0098.2018.02.016.
[45]
原福松,王勇,张耀鹏,等.口腔临床微机器人自动化牙体预备系统中全冠预备适宜参数初探[J].中华口腔医学杂志201752(5):270-273. DOI:10.3760/cma.j.issn.1002-0098.2017.05.002.
[46]
Yuan FWang YZhang Y,et al. An automatic tooth preparation technique:A preliminary study[J]. Sci Rep20166:25281. DOI:10.1038/srep25281.
[47]
Lerner HMouhyi JAdmakin O,et al. Artificial intelligence in fixed implant prosthodontics:A retrospective study of 106 implant-supported monolithic zirconia crowns inserted in the posterior jaws of 90 patients[J]. BMC Oral Health202020(1):80. DOI:10.1186/s12903-020-1062-4.
[48]
黄亚婷,左恩俊.基于虚拟现实技术在口腔修复中应用的数字化架[J].中国组织工程研究202024(22):3594-3601. DOI:10.3969/j.issn.2095-4344.2277.
[49]
Usui TMaki KToki Y,et al. Measurement of mechanical strain on mandibular surface with mastication robot:Influence of muscle loading direction and magnitude[J]. Orthod Craniofacial Res20036(Suppl 1):163-167. DOI:10.1034/j.1600-0544.2003.250.x.
[50]
Zhang YDGu JTJiang JG,et al. Motion control point optimization of dental arch generator[J]. Int J U-E-Serv Sci Technol20136(5):49-56. DOI:10.14257/ijunesst.2013.6.5.05.
[51]
Batra PTagra HKatyal S. Artificial intelligence in teledentistry[J]. Discoveries(Craiova)202210(3):153. DOI:10.15190/d.2022.12.
[52]
中华人民共和国国务院.国务院关于印发《中国制造2025》的通知[EB/OL].(2015-05-19)[2022-08-29].

URL    
[53]
Mohammad-Rahimi HMotamedian SRPirayesh Z,et al. Deep learning in periodontology and oral implantology:A scoping review[J]. J Periodontal Res202257(5):942-951. DOI:10.1111/jre.13037.
[54]
Schneider LRischke RKrois J,et al. Federated vs local vs central deep learning of tooth segmentation on panoramic radiographs[J]. J Dent2023135:104556. DOI:10.1016/j.jdent.2023.104556.
[55]
Kumar PRavindranath KSrilatha V,et al. Analysis of advances in research trends in robotic and digital dentistry:An original research[J]. J Pharm Bioallied Sci202214(Suppl 1):S185-S187. DOI:10.4103/jpbs.jpbs_59_22.
[56]
于海洋,张呐,贺子敬,等.弱人工智能数字化时代下的医技关系[J].口腔医学202343(7):577-583. DOI:10.13591/j.cnki.kqyx.2023.07.001.
[1] 李洋, 蔡金玉, 党晓智, 常婉英, 巨艳, 高毅, 宋宏萍. 基于深度学习的乳腺超声应变弹性图像生成模型的应用研究[J/OL]. 中华医学超声杂志(电子版), 2024, 21(06): 563-570.
[2] 杨敬武, 周美君, 陈雨凡, 李素淑, 何燕妮, 崔楠, 刘红梅. 人工智能超声结合品管圈活动对低年资超声医师甲状腺结节风险评估能力的作用[J/OL]. 中华医学超声杂志(电子版), 2024, 21(05): 522-526.
[3] 罗刚, 泮思林, 孙玲玉, 李志新, 陈涛涛, 乔思波, 庞善臣. 一种新型语义网络分析模型对室间隔完整型肺动脉闭锁和危重肺动脉瓣狭窄胎儿右心发育不良程度的评价作用[J/OL]. 中华医学超声杂志(电子版), 2024, 21(04): 377-383.
[4] 明昊, 肖迎聪, 巨艳, 宋宏萍. 乳腺癌风险预测模型的研究现状[J/OL]. 中华乳腺病杂志(电子版), 2024, 18(05): 287-291.
[5] 叶莉, 杜宇. 深度学习在牙髓根尖周病临床诊疗中的应用[J/OL]. 中华口腔医学研究杂志(电子版), 2024, 18(06): 351-356.
[6] 孙伯阳, 翟家彬, 黄兰柱, 郭婷. 数字化技术引导正畸牵引治疗冠根折牙齿的临床应用初探[J/OL]. 中华口腔医学研究杂志(电子版), 2024, 18(05): 330-335.
[7] 谢馨, 李一鸣, 胡晓均, 邓飞龙. 高压蒸汽灭菌次数对钛基底-聚醚醚酮种植扫描杆扫描准确度的影响[J/OL]. 中华口腔医学研究杂志(电子版), 2024, 18(04): 230-236.
[8] 王淑君, 张楚晗, 唐一阳, 赵雨桐, 李佳伦, 付佳乐. 自粘接树脂水门汀的临床应用及展望[J/OL]. 中华口腔医学研究杂志(电子版), 2024, 18(04): 276-286.
[9] 熊鹰, 林敬莱, 白奇, 郭剑明, 王烁. 肾癌自动化病理诊断:AI离临床还有多远?[J/OL]. 中华腔镜泌尿外科杂志(电子版), 2024, 18(06): 535-540.
[10] 李伟, 宋子健, 赖衍成, 周睿, 吴涵, 邓龙昕, 陈锐. 人工智能应用于前列腺癌患者预后预测的研究现状及展望[J/OL]. 中华腔镜泌尿外科杂志(电子版), 2024, 18(06): 541-546.
[11] 黄俊龙, 李文双, 李晓阳, 刘柏隆, 陈逸龙, 丘惠平, 周祥福. 基于盆底彩超的人工智能模型在女性压力性尿失禁分度诊断中的应用[J/OL]. 中华腔镜泌尿外科杂志(电子版), 2024, 18(06): 597-605.
[12] 莫淇舟, 苏劲, 黄健, 李健维, 李思宁, 柳建军. 智能控压输尿管软镜碎石吸引取石术在直径10~25 mm上尿路结石中的应用[J/OL]. 中华腔镜泌尿外科杂志(电子版), 2024, 18(05): 497-502.
[13] 李义亮, 苏拉依曼·牙库甫, 麦麦提艾力·麦麦提明, 克力木·阿不都热依木. 机器人与腹腔镜食管裂孔疝修补术联合Nissen 胃底折叠术短期疗效分析[J/OL]. 中华疝和腹壁外科杂志(电子版), 2024, 18(05): 512-517.
[14] 孙铭远, 褚恒, 徐海滨, 张哲. 人工智能应用于多发性肺结节诊断的研究进展[J/OL]. 中华临床医师杂志(电子版), 2024, 18(08): 785-790.
[15] 杨松林, 黄仕豪, 王丽珠, 李禧萌, 邹飞翔, 李坤炜, 梁明柱, 陈炳辉. 良性肺结节生长变化的影像学评价[J/OL]. 中华介入放射学电子杂志, 2024, 12(04): 344-350.
阅读次数
全文


摘要


AI


AI小编
你好!我是《中华医学电子期刊资源库》AI小编,有什么可以帮您的吗?