Clinical Research Directory

Rebooting Infant Pain Care: Using Machine Learning and Skin-to-Skin Contact to Exponentially Improve Neonatal Intensive Care Unit Practice

Sponsor: York University

Summary

To address the current limitations related to infant pain assessment in the NICU, our international team of knowledge users and health/natural science/engineering/social science researchers have come together to build a machine learning algorithm that will learn how to discriminate invasive and non-invasive distress. Furthermore, to improve the use of current pain management practices, our team seeks to better understand the developmental mechanisms underlying skin-to-skin contact over time and factors that may influence its efficacy in mitigating pain responses in preterm infants. This is an ongoing naturalistic observational study.

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