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AI-based feedback system for neonatal resuscitation: a feasibility and pilot study in Japan and Bhutan

bmjinnov · 2026-05-19 · canonical JSON source

3 visible annotations · policy: published · automated confidence ≥ 75.00%

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Approximately 15% of newborns are not breathing on their own at birth, requiring immediate resuscitation. 1 Since newborns can quickly develop asphyxia, marked by respiratory and circulatory failure, the first minute after birth is often referred to as the ‘Golden Minute’. During this critical period, it is essential to administer appropriate resuscitation measures without delay. Neonatal asphyxia accounts for an estimated 900 000 deaths annually, making it one of the leading causes of newborn mortality.2 In response, initiatives such as Helping Babies Breathe (HBB) were introduced to train healthcare providers in resource-limited settings.3 HBB focuses on the decision-making and procedures that must be performed during the Golden Minute, teaching basic neonatal resuscitation techniques. Although the HBB algorithm provides structured guidance for resuscitation, issues such as a shortage of adequately trained personnel and insufficient training opportunities leading to improper use of medical equipment remain prevalent.4