Progress in the application of artificial intelligence in the diagnosis and treatment of maxillofacial fractures

Maxillofacial fractures are common and frequently occurring diseases in Oral and Maxillofacial Surgery. The traditional clinical diagnosis and treatment process is easily affected by complex maxillofacial anatomy and differences in doctors’ experience in reading X-rays and making diagnoses. In recent years, artificial intelligence technology has provided new solutions for the accurate diagnosis and treatment planning of maxillofacial fractures. Automating image analysis through computer vision methods improves diagnostic accuracy and efficiency and assists in formulating treatment plans, showing broad application prospects and value. This article reviews and summarizes the research on the application of artificial intelligence in the auxiliary diagnosis and treatment of maxillofacial fractures at home and abroad, analyzes its advantages and disadvantages, and looks forward to future research trends.

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Publication Details

Journal
SHILAP Revista de lepidopterología
Published
2025-05-01
DOI
https://doi.org/10.13591/j.cnki.kqyx.2025.05.012
Primary Topic
Mycorrhizal Fungi and Plant Interactions
Type
article
Field-Weighted Citation Impact
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article

Progress in the application of artificial intelligence in the diagnosis and treatment of maxillofacial fractures

SHILAP Revista de lepidopterología
Mycorrhizal Fungi and Plant Interactions
article

Progress in the application of artificial intelligence in the diagnosis and treatment of maxillofacial fractures

article en

Abstract

Maxillofacial fractures are common and frequently occurring diseases in Oral and Maxillofacial Surgery. The traditional clinical diagnosis and treatment process is easily affected by complex maxillofacial anatomy and differences in doctors’ experience in reading X-rays and making diagnoses. In recent years, artificial intelligence technology has provided new solutions for the accurate diagnosis and treatment planning of maxillofacial fractures. Automating image analysis through computer vision methods improves diagnostic accuracy and efficiency and assists in formulating treatment plans, showing broad application prospects and value. This article reviews and summarizes the research on the application of artificial intelligence in the auxiliary diagnosis and treatment of maxillofacial fractures at home and abroad, analyzes its advantages and disadvantages, and looks forward to future research trends.

SHILAP Revista de lepidopterología
Children's Hospital of Zhejiang University (CN)
Quality Education
Openalex Percentile: Top 47%
Mycorrhizal Fungi and Plant Interactions
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