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Applications of artificial intelligence for surgical extraction in stomatology: a systematic review.
Qiu, Piaopiao; Cao, Rongkai; Li, Zhaoyang; Huang, Jiaqi; Zhang, Huasheng; Zhang, Xueming.
Affiliation
  • Qiu P; Department of Oral and Maxillofacial Surgery, Shanghai Engineering Research Center of Tooth Restoration and Regeneration & Tongji Research Institute of Stomatology, Stomatological Hospital and Dental School, Tongji University, Shanghai, China.
  • Cao R; Department of Oral and Maxillofacial Surgery, Shanghai Engineering Research Center of Tooth Restoration and Regeneration & Tongji Research Institute of Stomatology, Stomatological Hospital and Dental School, Tongji University, Shanghai, China.
  • Li Z; Department of Oral and Maxillofacial Surgery, Shanghai Engineering Research Center of Tooth Restoration and Regeneration & Tongji Research Institute of Stomatology, Stomatological Hospital and Dental School, Tongji University, Shanghai, China.
  • Huang J; Department of Oral and Maxillofacial Surgery, Shanghai Engineering Research Center of Tooth Restoration and Regeneration & Tongji Research Institute of Stomatology, Stomatological Hospital and Dental School, Tongji University, Shanghai, China.
  • Zhang H; Department of Oral and Maxillofacial Surgery, Shanghai Engineering Research Center of Tooth Restoration and Regeneration & Tongji Research Institute of Stomatology, Stomatological Hospital and Dental School, Tongji University, Shanghai, China.
  • Zhang X; Department of Oral and Maxillofacial Surgery, Shanghai Engineering Research Center of Tooth Restoration and Regeneration & Tongji Research Institute of Stomatology, Stomatological Hospital and Dental School, Tongji University, Shanghai, China. Electronic address: zhangxm@tongji.edu.cn.
Article in En | MEDLINE | ID: mdl-38834501
ABSTRACT

OBJECTIVES:

Artificial intelligence (AI) has been extensively used in the field of stomatology over the past several years. This study aimed to evaluate the effectiveness of AI-based models in the procedure, assessment, and treatment planning of surgical extraction. STUDY

DESIGN:

Following Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines, a comprehensive search was conducted on the Web of Science, PubMed/MEDLINE, Embase, and Scopus databases, covering English publications up to September 2023. Two reviewers performed the study selection and data extraction independently. Only original research studies utilizing AI in surgical extraction of stomatology were included. The Cochrane risk of bias tool for randomized trials (RoB 2) was selected to perform the quality assessment of the selected literature.

RESULTS:

From 2,336 retrieved references, 35 studies were deemed eligible. Among them, 28 researchers reported the pioneering role of AI in segmentation, classification, and detection, aligning with clinical needs. In addition, another 7 studies suggested promising results in tooth extraction decision-making, but further model refinement and validation were required.

CONCLUSIONS:

Integration of AI in stomatology surgical extraction has significantly progressed, enhancing decision-making accuracy. Combining and comparing algorithmic outcomes across studies is essential for determining optimal clinical applications in the future.
Subject(s)

Full text: 1 Database: MEDLINE Main subject: Tooth Extraction / Artificial Intelligence Limits: Humans Language: En Journal: Oral Surg Oral Med Oral Pathol Oral Radiol Year: 2024 Type: Article Affiliation country: China

Full text: 1 Database: MEDLINE Main subject: Tooth Extraction / Artificial Intelligence Limits: Humans Language: En Journal: Oral Surg Oral Med Oral Pathol Oral Radiol Year: 2024 Type: Article Affiliation country: China