Artificial Intelligence and Postpartum Hemorrhage.

Area of Science:

• Medical Informatics
• Artificial Intelligence in Healthcare
• Maternal Health

Background:

• Postpartum hemorrhage (PPH) is a major cause of maternal mortality globally.
• Despite advancements, PPH remains a significant challenge, even in developed countries.
• Artificial intelligence (AI) is increasingly explored for healthcare applications.

Purpose of the Study:

• To explore the application of AI in predicting and managing postpartum hemorrhage (PPH).
• To review current AI models for PPH risk stratification and identify limitations.
• To highlight future research directions for AI in PPH management.

Main Methods:

• Review of existing studies on AI applications in PPH prediction and management.
• Analysis of AI model performance, validation challenges, and applicability in different settings.
• Exploration of novel AI approaches, including uterine contractility and radiomics.

Main Results:

• Some AI models show promising results in predicting PPH, but external validation is often lacking.
• Current research is predominantly from well-resourced settings, with limited models for resource-limited areas.
• AI is also being investigated for blood product management and early detection via wearables.

Conclusions:

• AI offers significant potential for improving PPH prediction and management.
• Key challenges include model validation, clinical translation, and ensuring applicability across diverse healthcare systems.
• Further research, particularly in low- and middle-income countries, is essential to harness AI's full potential for global PPH reduction.