Artificial intelligence applications in allergic rhinitis diagnosis: Focus on ensemble learning.

Journal: Asia Pacific allergy
Published Date: Dec 18, 2023

Abstract

BACKGROUND: The diagnosis of allergic rhinitis (AR) primarily relies on symptoms and laboratory examinations. Due to limitations in outpatient settings, certain tests such as nasal provocation tests and nasal secretion smear examinations are not routinely conducted. Although there are clear diagnostic criteria, an accurate diagnosis still requires the expertise of an experienced doctor, considering the patient's medical history and conducting examinations. However, differences in physician knowledge and limitations of examination methods can result in variations in diagnosis.

Authors

  • Dai Fu
    Department of Otorhinolaryngology, Antin Hospital, Shanghai, China.
  • Zhao Chuanliang
    Department of Otorhinolaryngology-Head and Neck Surgery, Tongji Hospital, Tongji University School of Medicine, Shanghai, China.
  • Yang Jingdong
    School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai, China.
  • Meng Yifei
    School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai, China.
  • Tan Shiwang
    Department of Otorhinolaryngology-Head and Neck Surgery, Tongji Hospital, Tongji University School of Medicine, Shanghai, China.
  • Qian Yue
    Department of Otorhinolaryngology, Antin Hospital, Shanghai, China.
  • Yu Shaoqing
    Department of Otorhinolaryngology-Head and Neck Surgery, Tongji Hospital, Tongji University School of Medicine, Shanghai, China.

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