Machine-learning competition to grade EEG background patterns in newborns with hypoxic-ischaemic encephalopathy
PositiveArtificial Intelligence
A new machine-learning competition aims to enhance the grading of EEG background patterns in newborns suffering from hypoxic-ischaemic encephalopathy. This initiative is crucial as it provides researchers with access to high-quality, annotated data, which is often scarce. By fostering collaboration and direct comparisons of models, this competition not only supports the development of more accurate monitoring tools but also has the potential to significantly improve outcomes for at-risk newborns.
— Curated by the World Pulse Now AI Editorial System


