Predicting Flow Rate Escalation for Pediatric Patients on High Flow Nasal Cannula Using Machine Learning

• Main Authors: Joshua A. Krachman (Author), Jessica A. Patricoski (Author), Christopher T. Le (Author), Jina Park (Author), Ruijing Zhang (Author), Kirby D. Gong (Author), Indranuj Gangan (Author), Raimond L. Winslow (Author), Joseph L. Greenstein (Author), James Fackler (Author), Anthony A. Sochet (Author), Jules P. Bergmann (Author)
• Format: Book
• Published: Frontiers Media S.A., 2021-11-01T00:00:00Z.
• Subjects: article
• Online Access: Connect to this object online.

Background: High flow nasal cannula (HFNC) is commonly used as non-invasive respiratory support in critically ill children. There are limited data to inform consensus on optimal device parameters, determinants of successful patient response, and indications for escalation of support. Clinical scores...