Retrospective Study on the Direction of Artificial Intelligence in Identifying Cranial Trauma CT Imaging
- Conditions
- Cerebral Hemorrhage
- Registration Number
- NCT06230419
- Lead Sponsor
- RenJi Hospital
- Brief Summary
The goal of this observational retrospective study is to evaluate artificial intelligences (AI)'s proficiency in identifying and annotating brain bleeds in computed tomography (CT) images.
The main questions it aims to answer are:
* Whether AIs at present are capable of analyzing and recognizing cerebral traumas in CT images?
* If they are, how competent are they and how can humans take advantages of that? CT images were selected during the normal diagnosis and treatment process of patients, and no one needed to undergo any additional procedures connected to the study.
- Detailed Description
Not available
Recruitment & Eligibility
- Status
- ACTIVE_NOT_RECRUITING
- Sex
- All
- Target Recruitment
- 208
- People who had cerebral traumas with brain bleedings shown in CT images.
- Brain bleedings were not clear or representative in CT images.
Study & Design
- Study Type
- OBSERVATIONAL
- Study Design
- Not specified
- Primary Outcome Measures
Name Time Method The identification completeness of the annotated images. 1 months Use Photoshop to calculate the area of hemorrhage and the marked area, and then computing the ratio, import into Graphpad Prism for further analysis of the mean percentage and the standard deviation.
- Secondary Outcome Measures
Name Time Method The evaluations from professionals for outcomes produced by AIs 1 months The outputs will be evaluated by professional radiologists on a 4-point scale questionnaire from the completeness, accuracy and success of the annotation. Then the results of the questionnaire will be further analyzed in the Graphpad Prism to get the average score and the standard deviation.
Trial Locations
- Locations (1)
Brain Injury Center, Renji Hospital, School of Medicine, Shanghai Jiao Tong University
🇨🇳Shanghai, Shanghai, China