GE HealthCare – The grant from the Bill & Melinda Gates Foundation will facilitate the development of AI-assisted applications and tools to enable healthcare professionals with less experience to perform quick and accurate ultrasound scans to help address maternal and fetal health and respiratory diseases.
AI-assisted ultrasound algorithms will be developed to run on multiple ultrasound devices to expand access to high-quality care around the world with an emphasis on low- and middle-income countries (LMIC).
GE Healthcare (Nasdaq: GEHC) today announced it received a grant from the Bill & Melinda Gates Foundation for more than $44 million to create user-friendly, artificial intelligence (AI)-assisted ultrasound imaging auto-assessment tools.
These tools will seek to aid healthcare professionals—even those without specialized training or experience with ultrasound—with clinical decision information to support more effective obstetric and lung screening ultrasound scans across maternal and fetal care as well as pediatric lung health, with a goal of expanding access to low-and-middle-income countries (LMIC) and across diverse sites of care.
Caption Health, a leader in medical AI acquired by GE HealthCare in February 2023, will design this technology to run across a range of ultrasound devices and probes, including lower-cost handheld devices.
“We are proud and excited to have received this grant from the Bill & Melinda Gates Foundation to make ultrasound more accessible in low- and middle-income countries.
Ultrasound is an essential tool for screening and diagnosis of various medical conditions, including the health of expectant mothers and managing respiratory diseases,” said Roland Rott, President and CEO, of Ultrasound, GE HealthCare.
“However, a key limitation is the guidance of lesser-skilled users to effectively apply affordable point-of-care ultrasound in their care environment. This grant will help bring Caption Health’s leading AI technology customized to more users, and therefore contribute to increased access to higher-quality medical care.”
Maternal and child mortality is a critical healthcare issue around the world. In 2020, almost 800 women died every day from preventable causes linked to pregnancy and childbirth, with approximately 95 percent of all maternal deaths occurring in LMIC. In 2019, 2.4 million children around the world died in their first month of life.
Ultrasound technologies are used in maternal care to determine fetal health markers and conditions like gestational age, fetal presentation, multiple gestation (more than one fetus), fetal viability, umbilical blood flow, and ectopic pregnancy.
Bill & Melinda Gates Foundation Grant To Develop AI-Assisted Ultrasound Technology
For children younger than five years old, pneumonia is the leading cause of death worldwide. Because symptoms of pneumonia can develop suddenly, early diagnosis is vital to effective treatment and preventing complications.
Point-of-care lung ultrasound can provide physicians with a view of the entire lung, is easily repeatable and can diagnose pneumonia with greater accuracy compared with a bedside chest X-ray.
In 2020, Caption Health received a grant from the Bill & Melinda Gates Foundation to support the development of innovative AI technology for lung ultrasound.
“Caption Health AI applications are designed to guide healthcare professionals, step-by-step, during an ultrasound exam to help them capture and interpret high-quality ultrasound images,” said Karley Yoder, Chief Digital Officer, Ultrasound, GE HealthCare and General Manager, Caption Health.
“We are thankful for the continued support of the Bill & Melinda Gates Foundation, which enables us to expand the development of our existing lung ultrasound project and also broaden the reach of this powerful, novel technology to help provide care to mothers and children.”
Currently, Caption Health offers Cardiac Guidance software, which is FDA-cleared. With the support of the Bill & Melinda Gates Foundation grant, Caption Health will develop multiple lung ultrasound and obstetric algorithms through clinical validation and regulatory submissions.