The potential value of oral microbial signatures for prediction of oral squamous cell carcinoma based on machine learning algorithms.

Abstract

Authors

• Baochang He
  Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fuzhou, Fujian, China.
• Yujie Cao
  Department of Stomatology, The First Affiliated Hospital of Fujian Medical University, Fuzhou, Fujian, China.
• Zhaocheng Zhuang
  Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fuzhou, Fujian, China.
• Qingrong Deng
  Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fuzhou, Fujian, China.
• Yu Qiu
  The Xinjiang Technical Institute of Physics and Chemistry, Chinese Academy of Sciences, Urumqi, 830011, China.
• Lizhen Pan
  Department of Oral and Maxillofacial Surgery, The First Affiliated Hospital of Fujian Medical University, Fuzhou, Fujian, China.
• Xiaoyan Zheng
  Department of Oral and Maxillofacial Surgery, The First Affiliated Hospital of Fujian Medical University, Fuzhou, Fujian, China.
• Bin Shi
  Department of Materials Science and Engineering, University of Toronto, ON M5S 3H5, Canada. Electronic address: binmse.shi@mail.utoronto.ca.
• Lisong Lin
  Department of Oral and Maxillofacial Surgery, The First Affiliated Hospital of Fujian Medical University, Fuzhou, Fujian, China.
• Fa Chen
  Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fuzhou, Fujian, China.

Keywords

External Resources