Development of a Machine Learning program for Injury Surveillance in Children and Adolescents (BfU2.0)

Description

Background

Injuries in the age group of children and adolescents are a major public health concern and cause individual suffering and costs for the healthcare system and society. Evidence-based, targeted and effective injury prevention must be based on reliable data. Currently, this is not sufficiently guaranteed for injuries involving children and adolescents in Switzerland. This finding was confirmed in the feasibility study on data collection for injuries involving children and adolescents, which was carried out by the ZHAW on behalf of the BFU. It has also been shown that Machine Learning offers great potential for evaluating existing injury text data. This approach will be pursued further in the current project.

Aims

The overall objective of this follow-up project is to develop a Machine Learning (ML) programme based on digital patient records from a paediatric emergency department.

(Expected) Results

The results and the targeted data basis are intended to be used, among other things, for evidence-based injury prevention among children and adolescents.