Prediction models for early diagnosis of actinomycotic osteomyelitis of the jaw using machine learning techniques: a preliminary study.

Journal: BMC oral health
PMID: 35524204

Abstract

BACKGROUND: This study aimed to develop and validate five machine learning models designed to predict actinomycotic osteomyelitis of the jaw. Furthermore, this study determined the relative importance of the predictive variables for actinomycotic osteomyelitis of the jaw, which are crucial for clinical decision-making.

Authors

  • Sun-Gyu Choi
    Department of Oral and Maxillofacial Surgery, Hankook General Hospital, Danjae-ro 106, Sangdang-gu, Cheongju, South Korea.
  • Eun-Young Lee
    Department of Oral and Maxillofacial Surgery, College of Medicine and Medical Research Institute Chungbuk, National University, Chungdae-ro 1, Seowon-Gu, Cheongju, Chungbuk, 28644, South Korea.
  • Ok-Jun Lee
    Department of Pathology, Chungbuk National University Hospital, 776, 1Sunhwan-ro, Seowon-gu, Cheongju, Chungbuk, 28644, South Korea.
  • Somi Kim
    Dental Clinic Center, Chungnam National University Hospital, Sejong, South Korea.
  • Ji-Yeon Kang
    Department of Oral and Maxillofacial Surgery, College of Medicine, Chungnam National University, Daejeon, South Korea.
  • Jae Seok Lim
    Department of Oral and Maxillofacial Surgery, Chungbuk National University Hospital, 776, 1Sunhwan-ro, Seowon-gu, Cheongju, Chungbuk, 28644, South Korea. ahinshar1119@gmail.com.

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