This study aims to develop and validate a clinical prediction model for the risk of head and neck cancerous lesions using deep learning combined with AI algorithms, based on multi-center clinical data.
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The study cohort comprised outpatients and inpatients from the otolaryngology departments of the participating medical centers, who underwent laryngoscopy primarily for initial presenting symptoms such as pharyngeal discomfort and hoarseness.
Cohort
Prospective
Not listed
Laryngoscopic report diagnosis
those data will be collected via medical history records，"The laryngoscopic report diagnosis" primarily consists of detailed diagnostic classifications for various vocal fold and laryngeal pathologies.
Demographic data
Demographic data primarily includes demographic characteristics, behavioral habits, medical history, and lifestyle factors.
VHI-10
those data will be collected via questionnaire ，Voice-related quality of life was assessed using the Voice Handicap Index (VHI). Total scores range from 0 to 120. Higher scores indicate greater voice-related daily life handicap (worse outcome).
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The Affiliated Nanjing Drum Tower Hospital of Nanjing University Medical School
Lead sponsor
Taikang Xianlin Drum Tower Hospital
Collaborator
Zhongda Hospital
Collaborator
Affiliated Cixi Hospital of Wenzhou Medical University
Collaborator
Changzhou Fourth People's Hospital
Collaborator
Nanjing Tongren Hospital
Collaborator
Nanjing Children's Hospital
Collaborator
Gansu Provincial Maternal and Child Health Care Hospital
Collaborator
Shanghai Putuo District People's Hospital
Collaborator
Wuxi Huishan District People's Hospital
Collaborator
Fengyang County Hospital of Traditional Chinese Medicine
Collaborator
Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine
Collaborator
