Panel Speakers at SMFM AI Roundtable. Source: Ultrasound AI
Back to Articles

Articles Featured

Artificial Intelligence in Maternal-Fetal Medicine. Insights from a Panel Discussion. (AI in MFM)

The way patients are diagnosed, treated, and cared for is undergoing significant transformation in maternal-fetal medicine (MFM). Artificial intelligence (AI) is emerging as a powerful tool in enhancing diagnostic accuracy, optimizing workflows, and fostering equitable access to healthcare. But there are many profound implications of AI in MFM, which were discussed in a recent panel, “Exploring the Expanding Role of Artificial Intelligence in Maternal-Fetal Medicine” that featured clinicians and experts at the SMFM 2024 Pregnancy Meeting.

The speakers and panelists included: Jeanne Sottile, RDMS RVT CSPO of AS Software; University of Kentucky College of Medicine’s Maternal Fetal Medicine Fellow Physician, Dr. Neil Bharat Patel; CEO of Ultrasound AI, Robert Bunn; Chief Medical Offer and Professor, Dr. Garrett K.Lam, of Intermountain High Risk Pregnancy Center and University of Kentucky; and Martin Mienkina, PhD, Advanced Technology and Innovation Manager at GE Healthcare.

Here is a breakdown into the key insights that emerged of the multifaceted applications of AI, challenges, opportunities, and its potential to reshape patient outcomes.

The establishment of trust in algorithmic insights is central to the integration of AI into MFM.

Rigorous testing methodologies are paramount to validate AI algorithms, ensuring consistency and persistence of results across diverse patient populations and clinical settings.

Transparency and trust will build the foundation of successful adoption and utilization of new AI technologies, ensuring that AI-driven innovations enhance, rather than compromise, patient care.

A compelling aspect of AI in MFM is its capacity to democratize healthcare access.

By mitigating skill barriers through technologies like AI-assisted ultrasound, AI enables less specialized practitioners to perform basic examinations with greater accuracy. This innovation is especially promising for underserved rural and international communities, where access to specialized care can be limited.

AI algorithms, like those that can predict preterm birth, represent a large shift in diagnostic approaches.

These algorithms transcend conventional anatomical markers like the cervix, leveraging digital signals within ultrasound images to discern subtle patterns and correlations. AI can ‘see’ beyond human perception and analyze a spectrum of anatomical areas (like the ovaries, uterus, and placenta).

By processing vast amounts of data in real time, AI algorithms can detect early indicators of complications, leading to timelier interventions and improved patient outcomes.

Ensuring equitable access to AI-driven healthcare solutions is a critical consideration in the adoption of AI in MFM.

Some collaborative efforts underway include the development of solutions tailored for low-resource settings, supported by organizations like the Gates Foundation. By leveraging AI to bridge healthcare gaps globally, these initiatives aim to advance maternal and fetal health outcomes worldwide.

The equitable dissemination of AI solutions in MFM extends beyond merely providing access to technology. It involves tailoring solutions to suit the needs of diverse populations and addressing systemic barriers to healthcare access. By prioritizing inclusivity and accessibility, AI-driven innovations have the potential to revolutionize maternal and fetal healthcare delivery.

From enhancing diagnostic precision to optimizing workflows and fostering equitable access to healthcare, AI promises to transform patient care in MFM. However, realizing this potential requires collaborative efforts, rigorous testing methodologies, and regulatory oversight to ensure the reliability, validity, and accessibility of AI technologies.

As the healthcare industry navigates the intersection of AI and healthcare, the future of maternal-fetal medicine holds promise for improved patient outcomes and enhanced quality of care.


Learn more about AS Software’s approach to AI: AI in Ultrasound Reporting: Driving Efficiency and Automation