USING ARTIFICIAL INTELLIGENCE (AI) AND MACHINE LEARNING (ML) TO ELIMINATE PREVENTABLE MATERNAL MORTALITY: A CALL TO ACTION

This study reviewed maternal mortality. The problem is that preventable maternal mortality exists disproportionately among birthing people. The research question was “How can artificial intelligence (AI) and machine learning (ML) be used to eliminate preventable maternal mortality?” The purpose of this study was to identify and recommend a set of specific technologies, such as AI and ML, to decrease healthcare disparities in reproductive healthcare; significantly decrease maternal mortality rates; and encourage new healthcare policies eliminating healthcare disparities. The methodology was a scoping review.

The set of technological recommendations included mobile applications for patient contact; telehealth and other medical communications; digital maternal health platforms; patient monitoring devices; medical forecasting technologies; and the use of multimodal data. Each of these recommendations use some type of AI and ML. The results showed that predictive modeling is the core of AI that can be used to eliminate preventable maternal mortality for all birthing people, regardless of their demographics. Future research is required to build strong predictive modeling tools for implementation into maternal healthcare to lower maternal mortality rates. AI and ML can be used to eliminate preventable maternal mortality by using AI-powered tools to analyze and interpret data and to enhance the quality and accessibility of healthcare and by using ML algorithms for accurate predictions of perinatal health risks.

Keywords: maternal mortality, artificial intelligence (AI), machine learning (ML), maternal health, and pregnancy