Identifying neonatal seizures with an automatic algorithm


A new study in The Lancet: Child and Adolescent Health investigated the use of a machine-learning algorithm for neonatal seizure recognition.

The randomized, controlled trial was conducted to assess the diagnostic accuracy of the automated seizure detection algorithm, called Algorithm for Neonatal Seizure Recognition (ANSeR). Researchers sought to find out if ANSeR could help the method of continuous conventional electroencephalography (cEEG).

The researchers concluded that ANSeR was safe and could accurately detect neonatal seizures, but it did not improve the identification of seizures beyond cEEG. For more information on the study, visit Contemporary Pediatrics.

Related Videos
Addressing maternal health inequities: Insights from CDC's Wanda Barfield | Image Credit:
Addressing racial and ethnic disparities in brachial plexus birth Injury | Image Credit:
Innovations in prenatal care: Insights from ACOG 2024 | Image Credit:
raanan meyer, md
The impact of smoking cessation on pregnancy outcomes | Image Credit:
Maximizing maternal health: The impact of exercise during pregnancy | Image Credit:
The importance of nipocalimab’s FTD against FNAIT | Image Credit:
Fertility treatment challenges for Muslim women during fasting holidays | Image Credit:
CDC estimates of maternal mortality found overestimated | Image Credit:
Related Content
© 2024 MJH Life Sciences

All rights reserved.