A machine learning-based risk prediction model for diabetic oral ulceration.

Journal: BMC oral health
Published Date: May 22, 2025

Abstract

BACKGROUND: Diabetic oral ulceration (DOU) is a prevalent and debilitating complication among diabetic patients, significantly impairing their quality of life and imposing substantial economic burdens. Studies indicate that over 90% of diabetic patients experience oral complications, with 45% suffering from oral ulcers. Clear diagnosis is crucial for effective clinical management and prognosis improvement. However, current diagnostic methods often fall short in early detection and intervention. Machine learning (ML) has shown promise in predicting disease development, yet no relevant predictive models for DOU have been established.

Authors

  • Wang Xiaoling
    Department of Endocrinology, Xinhua Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200092, China.
  • Wang BingQian
    Intensive Care Unit, Suzhou TCM Hospital Affiliated to Nanjing University of Chinese Medicine, Suzhou, Jiangsu, 215009, China.
  • Zhu Zhenqi
    Science Teaching and Research Group, Konger Primary School, Shanghai, 200093, China.
  • Li Wen
  • Gu Shuyan
    Center for Health Policy and Management Studies, School of Government, Nanjing University, Nanjing, 210023, China.
  • Chen Hanbei
    Department of Endocrinology, Xinhua Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200092, China.
  • Xin Feng
    State Key Laboratory for Zoonotic Diseases, College of Veterinary Medicine, Jilin University, Changchun, China.
  • Chenglong Yang
    Department of Stomatology, Xinhua Hospital, Core Unit of National Clinical Research Center for Oral Diseases, Shanghai Jiao Tong University School of Medicine, Shanghai, 200092, China.
  • Jutang Li
    Hongqiao International Institute of Medicine, Tongren Hospital, Shanghai Jiao Tong University School of Medicine, 1111 XianXia Road, Shanghai, 200336, China.
  • Guoyao Tang
    Department of Stomatology, Xinhua Hospital, Core Unit of National Clinical Research Center for Oral Diseases, Shanghai Jiao Tong University School of Medicine, Shanghai, 200092, China.
  • Jie Wei
    Department of Computer Science, City College of New York, New York, USA.

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