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Difference between revisions of "AI-Assisted Quality Control of CTD Data"
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== Use Case Objectives == | == 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: | * Aspirational Goals: | ||
* Mitigation of uncertainty in human decisions | * Mitigation of uncertainty in human decisions | ||
Revision as of 10:07, 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
