6x Faster Video Annotation for King's College London

King's College London used Encord to achieve a 6.4x average increase in labeling efficiency for GI videos.

Problem

Using clinicians to annotate pre-cancerous polyp videos had prohibitively high costs to produce large datasets.

Solution

Deployed Encord's micro-model module to increase clinician labeling efficiency and automate 97% of produced labels.

Results

The highest-expense clinician saw a 16x labeling efficiency improvement. Cut model development time from 1 year to 2 months.

• 6.4X faster than manual labeling
• 97% automated labels
• 6X faster to AI in production