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Construction of AI Model for Precision Imaging Diagnosis of Cranial Diseases
Sponsor: Tongji Hospital
Summary
The goal of this observational study is to develop and validate a high-precision AI diagnostic model for cranial diseases by integrating clinical knowledge systems (pathophysiological classification, age stratification, and anatomical localization) to simulate radiologists' diagnostic thinking. The main question it aims to answer is: Does the AI model improve diagnostic accuracy and consistency across different hospital levels, physician qualifications, and clinical scenarios compared to traditional diagnosis? Participants' cranial MRI data (including T1, T2, FLAIR, DWI sequences) and clinical information will be collected retrospectively (2015-2025) and prospectively (2026) to train and validate the model, which will be evaluated through performance metrics (accuracy, sensitivity, specificity) and clinical efficacy assessments (doctor vs. model, with/without model assistance). This study will establish a new paradigm for clinical AI implementation, providing methodological support for precision diagnosis of neurological diseases.
Key Details
Gender
All
Age Range
Any - Any
Study Type
OBSERVATIONAL
Enrollment
1000
Start Date
2026-01-01
Completion Date
2026-12
Last Updated
2026-03-06
Healthy Volunteers
Yes
Locations (1)
Tongji Hospital
Wuhan, Hubei, China