Development of a machine learning-based predictive model for maxillary sinus cysts and exploration of clustering patterns.

Journal: Head & face medicine
PMID: 40069749

Abstract

BACKGROUND AND OBJECTIVE: There are still many controversies about the factors influencing maxillary sinus cysts and their clinical management. This study aims to construct a prediction model of maxillary sinus cyst and explore its clustering pattern by cone beam computerized tomography (CBCT) technique and machine learning (ML) method to provide a theoretical basis for the prevention and clinical management of maxillary sinus cyst.

Authors

  • Haoran Yang
    School of Medical Imaging, Binzhou Medical University, No. 346 Guanhai Road, Laishan District, Yantai, 264003, China.
  • Yuxiang Chen
    Laboratory of Lung, Xinglin Branch of the First Affiliated Hospital of Xiamen University, Xiamen 361022, Fujian, China.
  • Anna Zhao
    Affiliated Stomatology Hospital of Kunming Medical University, Kunming, Yunnan, China; Yunnan Provincial Key Laboratory of Stomatology, Kunming, Yunnan, China.
  • Xianqi Rao
    Affiliated Stomatology Hospital of Kunming Medical University, Kunming, Yunnan, China; Yunnan Provincial Key Laboratory of Stomatology, Kunming, Yunnan, China.
  • Lin Li
    Department of Medicine III, LMU University Hospital, LMU Munich, Munich, Germany.
  • Ziliang Li
    Affiliated Stomatology Hospital of Kunming Medical University, Kunming, Yunnan, China; Yunnan Provincial Key Laboratory of Stomatology, Kunming, Yunnan, China. 1752114604@qq.com.

Keywords

External Resources

Popular Topics
Recent Journals