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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)
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
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Decision of hypothermia | Other | Decision of hypothermia thanks to EEG signal |
| Measure | Description | Time Frame |
|---|---|---|
| Decision of hypothermia protocol start | Use of EEG signal in order to develop an algorithm | 6 months |
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Inclusion Criteria:
Exclusion Criteria:
-Opposition of parental authority holders of a patient born after 2015
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Babies born within a context of HIE (Hypoxic Ischemic Encephalopathy)
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Hôpital TROUSSEAU | Paris | 75012 | France |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 41260106 | Derived | Fiammante M, Vermersch AI, Vidailhet M, Chavez M. A simple EEG-based tool to guide therapeutic hypothermia decisions in neonatal hypoxic-ischemic encephalopathy. Comput Methods Programs Biomed. 2026 Feb 1;274:109166. doi: 10.1016/j.cmpb.2025.109166. Epub 2025 Nov 13. |
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| ID | Term |
|---|---|
| D001927 | Brain Diseases |
| ID | Term |
|---|---|
| D002493 | Central Nervous System Diseases |
| D009422 | Nervous System Diseases |
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