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Difference between revisions of "AI-Assisted Quality Control of CTD Data"
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* Business Value: Flagged scans allow the analyst to quickly focus attention on crucial areas, reducing the time and effort required to delete scans | * Business Value: Flagged scans allow the analyst to quickly focus attention on crucial areas, reducing the time and effort required to delete scans | ||
* Measures of Success: | * Measures of Success: | ||
| − | + | * Accuracy of model predictions | |
| − | + | * Client feedback on quality control speed-ups | |
* Aspirational Goals: | * Aspirational Goals: | ||
| − | + | * Mitigation of uncertainty in human decisions | |
| − | + | * Semi or full automation of scan deletions | |
Revision as of 10:06, 22 December 2022
Use Case Objectives
- Machine Learning Task: Flag in advance the scans to be deleted during CTD quality control
- Business Value: Flagged scans allow the analyst to quickly focus attention on crucial areas, reducing the time and effort required to delete scans
- Measures of Success:
* Accuracy of model predictions * Client feedback on quality control speed-ups
- Aspirational Goals:
* Mitigation of uncertainty in human decisions * Semi or full automation of scan deletions
Machine Learning Pipeline
Experimental Model Performance
Model Deployment and Integration
