NCT04723017

Perioperative Hypoxemia in Pediatrics

Development and Validation of Perioperative Hypoxemia Using Clinical Big Data and Deep Learning Technique in Pediatric Patients

• Status: Unknown
• Phase: —
• Study type: Observational
• Enrollment: 17,000 (estimated)
• Sponsor: Seoul National University Hospital · Academic / Other
• Sex: All
• Age: 19 Years
• Healthy volunteers: Not accepted

Summary

The primary aim was to develop and validation of perioperative hypoxemia using clinical big data and deep learning technique in pediatric patients

Conditions

• Hypoxemia

Interventions

Type	Name	Description
OTHER	Retrospective analysis cohort	We analyze pre-existing data base and develop machine-learning-based system that predicts the risk of hypoxemia
OTHER	Prospective validation cohort	We validate our model to predict the risk of hypoxemia to prospective cohort

Timeline

• Start date: 2021-01-21
• Primary completion: 2021-12-31
• Completion: 2021-12-31
• First posted: 2021-01-25
• Last updated: 2021-01-25

Locations

1 site across 1 country: South Korea