Understanding the circumstances of paediatric fall injuries: a machine learning analysis of NEISS narratives.

Elise OmakiWendy ShieldsMasoud RouhizadehPamela Delgado-BarrosoRuth StefanosAndrea Gielen

Published in: Injury prevention : journal of the International Society for Child and Adolescent Injury Prevention (2023)

The prevalence of injuries due to falling off the bed, and the elevated risk of serious injury from falling from another person highlights the need for more robust and effective communication to caregivers on fall injury prevention.

Keyphrases

machine learning
intensive care unit
palliative care
risk factors
artificial intelligence
big data
deep learning