AI Innovating Pregnancy Care and Cancer Screening


According to findings collected by Cedars-Sinai, artificial intelligence can reduce serious health risks associated with pregnancy and childbirth, and improve screening for some gynecological cancers.

Artificial Intelligence (AI) can reduce serious health risks associated with pregnancy and childbirth, and improve screening for some gynecological cancers, according to findings collected by Cedars-Sinai.

These findings came from studies that looked at the leading causes of death during pregnancy and childbirth: preeclampsia and postpartum hemorrhage (PPH).

Preeclampsia, a common complication of pregnancy, is characterized by high blood pressure and other symptoms like swelling and protein in the urine. It poses a grave risk to both mother and child.

© SurfupVector -

© SurfupVector -

PPH, the leading cause of maternal death globally, can occur after childbirth and requires immediate intervention.

One study conducted at Cedars-Sinai focused on leveraging AI to identify patients at risk of developing preeclampsia.

By using technology to prescribe aspirin — a known preventive medication — the study not only increased the appropriate use of aspirin but also eliminated racial disparities in care.

Historically, Black pregnant women have often been overlooked for aspirin treatment, regardless of being at increased risk.

The creation of a pop-up alert in patients' medical charts proved to be a game-changer, ensuring timely intervention and reducing the risk of adverse outcomes.

Melissa Wong, MD, a maternal-fetal medicine specialist at Cedars-Sinai and the brain behind the pop-up alert, highlighted the challenges faced by healthcare providers in a news release, which identified moderate-risk factors for preeclampsia.

This initiative led to the development of a solution that prompts OB-GYNs to consider aspirin therapy for patients with moderate-risk factors.

In another study, Cedars-Sinai researchers used AI and machine learning to predict severe complications from postpartum hemorrhage.

By analyzing data points throughout labor and delivery, including underlying medical conditions and anesthesia types, an algorithm was developed to identify patients at increased risk.

The ultimate goal and result was to enable real-time prediction of hemorrhages, reach timely intervention and potentially saving lives.

Looking ahead, Cedars-Sinai researchers are exploring further uses of AI in women’s health.

Studies are underway to enhance the evaluation of Pap smears for cervical cancer detection, manage gestational diabetes and hypertension during pregnancy.

Wong said in the release that “the primary goal of harnessing AI for healthcare is about how AI can help healthcare providers free up their brains and their time to focus on delivering the best possible care.

“It can be a remarkable tool that brings us front and center with the patient again and moves us away from the kind of work that AI and machine learning do more effectively, quickly and accurately.”

She added that if a provider may be in a healthcare desert with limited resources or at an academic medical center, the best applications of AI will have a significant impact — reducing healthcare inequalities and providing care that could be more personalized across patient populations.

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