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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 == | ||
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| + | * 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 | ||
| + | |||
| + | |||
[[File:Business process.png|Flow diagram for the model integration into the business process.]] | [[File:Business process.png|Flow diagram for the model integration into the business process.]] | ||
Revision as of 10:01, 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
