NCT05114070

Build a Decision Aid Tool to Help Emergency Intensive Care Specialists in the Context of Hypoxic Ischemic Encephalopathy

Build a Decision Aid Tool to Help Emergency Intensive Care Specialists in the Context of Hypoxic Ischemic Encephalopathy. NEWBORN NEURO-DIGITAL STUDY

• Status: Completed
• Phase: —
• Study type: Observational
• Enrollment: 106 (actual)
• Sponsor: Assistance Publique - Hôpitaux de Paris · Academic / Other
• Sex: All
• Age: 2 Days
• Healthy volunteers: Not accepted

Summary

The project aims at designing a machine learning solution able to recognize characteristics signals patterns of brain damages in full term babies born within a context of Hypoxic Ischemic Encephalopathy (HIE)

Detailed description

Retrospective study based on a digital EEG signal library intending to design, train and test an efficient AI solution for hypothermia protocol start indications. The output of the Project is to make available to pediatric resuscitation units an adequate tool to guide them in the decision of hypothermia protocol start in a general context of neurophysiologist competence scarcity. EEG signal that would allow the algorithm design will be based on several parameters of the conventional EEG and not only on signal amplitude

Conditions

• Encephalopathy

Interventions

Type	Name	Description
OTHER	Decision of hypothermia	Decision of hypothermia thanks to EEG signal

Timeline

• Start date: 2022-09-08
• Primary completion: 2023-09-08
• Completion: 2023-09-08
• First posted: 2021-11-09
• Last updated: 2024-02-05

Locations

1 site across 1 country: France