8 seconds
“with active learning and model-assisted workflows, the average dropped to 8 seconds”
As published on labelbox.com. Captured by usedby on Oct 7, 2026.
What happened
Advent Health Partners uses Labelbox as a data engine to turn unstructured medical records into labeled training data for its OCR and NLP models. It combines model-assisted workflows, active learning, and expert human review to classify pages and evaluate entity-extraction accuracy.
Summary written by usedby from the source page, in English. The figures are those of Labelbox and Advent Health Partners, not ours.
- 25 hours“we have been able to cut a full 25 hours we have been able to cut a full 25 hours from the process of generating high-quality AI data”
Classifying and providing expert feedback each page used to take about 13 seconds; with active learning and model-assisted workflows, the average dropped to 8 seconds.
By using Labelbox's model-assisted workflows, we have been able to cut a full 25 hours we have been able to cut a full 25 hours from the process of generating high-quality AI data, and we’ve found that our experts have an easier time through a software-first approach
What the story claims, and what we checked
We compared the story with its live page on Oct 7, 2026.
- The figure: 8 secondsCheckedPrinted word for word on the page, near the name of Advent Health Partners.
- The passage quoted aboveCheckedCopied word for word from the page, near the name of Advent Health Partners.
- Advent Health Partners uses LabelboxCheckedConfirmed line. Latest check across sources: Oct 7, 2026.
- The result itselfNot checkedWe quote it; we did not measure it.




