Artificial intelligence and informatics in neonatal resuscitation

Area of Science:

• Neonatal intensive care
• Medical informatics
• Artificial intelligence in healthcare

Background:

• Neonatal intensive care unit (NICU) resuscitative care is evolving, with increasing reliance on data.
• Current data underutilization stems from suboptimal data capture, aggregation, and low adoption of AI/analytics tools.

Purpose of the Study:

• To review the fundamentals and evidence for informatics and artificial intelligence (AI) tools in NICU resuscitative care.
• To explore applications in training and education for neonatal resuscitation.

Main Methods:

• Literature review of informatics and AI tools in neonatal resuscitation.
• Analysis of challenges in data capture, aggregation, and AI adoption.
• Examination of ethical considerations, including data privacy, bias, and liability.

Main Results:

• Effective interface design is needed for accurate data capture.
• Data must be stored and translated into actionable insights using analytics and AI.
• Key challenges include data privacy, bias, liability, and ethical frameworks.

Conclusions:

• Informatics and AI hold significant promise for improving neonatal resuscitation.
• Further research on these applications in the neonatal population is essential.
• Increased awareness of informatics and AI principles among clinicians is imperative for successful adoption.