Development of AI-Based Diagnostic Algorithm for Nasal Bone Fracture Using Deep Learning

被引:4
|
作者
Jeong, Yeonjin [1 ]
Jeong, Chanho [2 ]
Sung, Kun-Yong [2 ]
Moon, Gwiseong [3 ]
Lim, Jinsoo [4 ]
机构
[1] Natl Med Ctr, Dept Plast & Reconstruct Surg, Seoul, South Korea
[2] Kangwon Natl Univ Hosp, Dept Plast & Reconstruct Surg, Kangwon Do, South Korea
[3] Kangwon Natl Univ, Dept Comp Sci & Engn, Kangwon Do, South Korea
[4] Catholic Univ Korea, Coll Med, St Vincents Hosp, Dept Plast & Reconstruct Surg, 93 Jungbu Daero, Suwon 16247, Gyeonggi Do, South Korea
关键词
Artificial intelligence; deep learning; facial bone CT; nasal bone fracture;
D O I
10.1097/SCS.0000000000009856
中图分类号
R61 [外科手术学];
学科分类号
摘要
Facial bone fractures are relatively common, with the nasal bone the most frequently fractured facial bone. Computed tomography is the gold standard for diagnosing such fractures. Most nasal bone fractures can be treated using a closed reduction. However, delayed diagnosis may cause nasal deformity or other complications that are difficult and expensive to treat. In this study, the authors developed an algorithm for diagnosing nasal fractures by learning computed tomography images of facial bones with artificial intelligence through deep learning. A significant concordance with human doctors' reading results of 100% sensitivity and 77% specificity was achieved. Herein, the authors report the results of a pilot study on the first stage of developing an algorithm for analyzing fractures in the facial bone.
引用
收藏
页码:29 / 32
页数:4
相关论文
共 50 条
  • [41] Precision agriculture with AI-based responsive monitoring algorithm
    Dusadeerungsikul, Puwadol Oak
    Nof, Shimon Y.
    INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS, 2024, 271
  • [42] Precision agriculture with AI-based responsive monitoring algorithm
    Department of Industrial Engineering, Faculty of Engineering, Chulalongkorn University, Bangkok, Thailand
    不详
    IN, United States
    Int J Prod Econ, 2024,
  • [43] Automated Data Annotation for 6-DoF AI-Based Navigation Algorithm Development
    Baca, Javier Gibran Apud
    Jantos, Thomas
    Theuermann, Mario
    Hamdad, Mohamed Amin
    Steinbrener, Jan
    Weiss, Stephan
    Almer, Alexander
    Perko, Roland
    JOURNAL OF IMAGING, 2021, 7 (11)
  • [44] AI-Based Crop Disease Detection: Evaluation of Wheat Rust Disease Detection and Classification Using Deep Learning and Machine Learning Approaches
    Akinosun, Temitayo
    Nibouche, Omar
    2023 31ST IRISH CONFERENCE ON ARTIFICIAL INTELLIGENCE AND COGNITIVE SCIENCE, AICS, 2023,
  • [45] The Development and Validation of an AI Diagnostic Model for Sacroiliitis: A Deep-Learning Approach
    Lee, Kyu-Hong
    Lee, Ro-Woon
    Lee, Kyung-Hee
    Park, Won
    Kwon, Seong-Ryul
    Lim, Mie-Jin
    DIAGNOSTICS, 2023, 13 (24)
  • [46] Translational AI and Deep Learning in Diagnostic Pathology
    Serag, Ahmed
    Ion-Margineanu, Adrian
    Qureshi, Hammad
    McMillan, Ryan
    Saint Martin, Marie-Judith
    Diamond, Jim
    O'Reilly, Paul
    Hamilton, Peter
    FRONTIERS IN MEDICINE, 2019, 6
  • [47] Using an AI-Based Object Detection Translation Application for English Vocabulary Learning
    Liu, Pei-Lin
    Chen, Chiu-Jung
    EDUCATIONAL TECHNOLOGY & SOCIETY, 2023, 26 (03): : 5 - 20
  • [48] AI-Based Intelligent Model to Predict Epidemics Using Machine Learning Technique
    Ali, Liaqat
    Alnawayseh, Saif E. A.
    Salahat, Mohammed
    Ghazal, Taher M.
    Tomh, Mohsen A. A.
    Mago, Beenu
    INTELLIGENT AUTOMATION AND SOFT COMPUTING, 2023, 36 (01): : 1095 - 1104
  • [49] Identifying presence of cybersickness symptoms using AI-based predictive learning algorithms
    Zaidi, Syed Fawad M.
    Shafiabady, Niusha
    Beilby, Justin
    VIRTUAL REALITY, 2023, 27 (04) : 3613 - 3620
  • [50] Identifying presence of cybersickness symptoms using AI-based predictive learning algorithms
    Syed Fawad M. Zaidi
    Niusha Shafiabady
    Justin Beilby
    Virtual Reality, 2023, 27 : 3613 - 3620