April 25, 2025

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Smart Solutions, Bright Future

The Scientist Using AI to Improve Maternal Health

The Scientist Using AI to Improve Maternal Health

When Maryam Mustafa walked into a small, crowded clinic in Pakistan she carefully scanned the space—a shared lobby that doubled as an examination room. Dozens of women waited quietly as doctors moved from patient to patient. Each woman had only moments to explain why she was there before the physician moved on. Mustafa observed the interactions closely.

“[Doctors] have three minutes per patient,” she says. “They only have the bandwidth to ask, ‘Why are you here today?’”

For many Pakistani women who are pregnant, this kind of visit is their first and only prenatal medical appointment, which puts them at increased risk of life-threatening conditions like preeclampsia, anemia and gestational diabetes. Early detection can save lives, but the lack of affordable and accessible care, health clinic workers’ limited time with each patient, and lack of privacy in under resourced clinics can lead to a deadly gap in care for mothers and their unborn children.


[Doctors] have three minutes per patient. They only have the bandwidth to ask, ‘Why are you here today?’

Maryam Mustafa


Co-founder


Awaaz-e-Sehat






“This happens so often, where women come in for a first visit and then you don’t see them again until they land in the emergency room, often when it’s too late,” Mustafa says.

She was in the clinic that day for an important reason—one that could help transform maternal health care in low-resource settings. As a computer scientist dedicated to accelerating progress in health and development, she was developing accessible, cheap technology to help health workers detect pregnancy risks early and save the lives of mothers and babies. In Pakistan, more than 150 women die for every 100,000 live births—each one a mother who might have been saved with timely care.

A path where human needs and technology meet

In Mustafa’s Pakistani family, education came first. “My parents were an anomaly in how they raised their daughters,” she says. They insisted that all six of their children—their daughters as well as their sons—have access to the very best educational opportunities. But for Mustafa, choosing a path wasn’t simple.


Maryam Mustafa (2L) speaks with colleagues in Lahore, Pakistan.

Maryam Mustafa (2L) speaks with colleagues in Lahore, Pakistan.



At Lahore University of Management Sciences (LUMS), one of Pakistan’s top universities, she majored in computer science, albeit reluctantly. She excelled as an undergraduate but felt that something was missing. “There’s always been this inherent friction in my life,” she says. “I was always interested in anthropology and sociology. I wanted to understand people’s lives.”

Though trained as a computer scientist at top universities in Pakistan, the U.S., and Germany, Mustafa was drawn to the human side of technology. Her passion for anthropology and design led her to specialize in human-computer interaction—a field that blends people, psychology, and innovation.

A maternal health solution powered by artificial intelligence

Mustafa’s work to improve maternal health care began with years of on-the-ground research. She visited clinics and hospitals and spoke to countless women, seeking to understand why so many were dying from preventable conditions like high blood pressure, which leads to eclampsia—one of the leading causes of maternal mortality in Pakistan.

The answer became clear: Critical symptoms were being missed due to rushed consultations, overworked doctors, and lack of access to trained health care workers which led to delayed or missed diagnoses.

To help solve this, Mustafa and her team developed Awaaz-e-Sehat—“Voice of Health” in Urdu—a voice-assisted app designed specifically for frontline health workers. Using simple smartphones, the app guides providers through structured questions in local languages, helping them identify warning signs of conditions like pre-eclampsia or gestational diabetes during brief consultations. By capturing patient responses in real time and flagging potential risks, the tool supports more attentive, informed care—even in the most resource-strapped settings.

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