Study
            
                NLST
                (Learn more about this study)
            
 
            
            
                Project ID
                
                    
                        NLST-1186
                    
                
            
            
                Initial CDAS Request Approval
                Jan 11, 2024
            
            Title
            The Practical Application of the Lung Cancer Risk Prediction Model 'Sybil': Replicating and Validating Study Results in Taiwan
            
                Summary
                Our intention is to replicate and validate the findings of the paper titled "Sybil: A Validated Deep Learning Model to Predict Future Lung Cancer Risk From a Single Low-Dose Chest Computed Tomography." This study demonstrated promising results, which prompts our interest in applying this method to the NLST dataset and beyond. Our ultimate goal is to reproduce the model outlined in the paper and adapt it for real-world uses in Taiwan.
            
            
                Aims
                1.Reproduce the Sybil model using the NLST dataset to replicate its findings.
2. Implement the Sybil model in practical healthcare settings within Taiwan.
Collaborators
                
                Tsung-Ren Huang, National Taiwan University
Chun-Rong Huang, National Cheng Kung University