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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.

Rigorous Testing is Needed

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.

The Potential of Democratizing Healthcare Access

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.

Going Beyond Conventional Anatomical Markers

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.

The Equitable Dissemination of AI Solutions

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.

The Transformative Potential of AI in MFM is Undeniable

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

Artificial Intelligence (AI) has the potential to reshape the ultrasound technology landscape — revolutionizing patient care, enhancing diagnostic accuracy, and transforming the use of ultrasound technology.

“The integration of artificial intelligence technology in ultrasound imaging is expected to make the ultrasound imaging technique smarter and improve the efficiency of the technique to accurately examine the disease. The surging demand for imaging biomarkers and quantitative imaging is significantly driving the demand for AI in ultrasound imaging.” (Precedence Research)

Current ultrasound reporting solutions drive value through greater efficiency, automation, and interoperability. These same benefits are also major catalysts of emerging AI value, which will continue to drive clinical, financial, and operational benefits for healthcare organizations.

How AI can complement our existing workflow solution

AS Software is the workflow conduit connecting ultrasound machines, EHRs, and PACS/VNA, and we’re uniquely positioned to incorporate AI into this existing solution ecosystem deployed across our customer base — which currently manages over 10 million studies annually.

We have a long track record of prioritizing interoperability with industry-leading technology providers; many of which are now incorporating AI into their offerings. AS Software will be positioned to both interoperate with existing AI and leverage embedded AI from various partners in the market.

We’re excited to have customers and partners working with us to explore options to best meet these needs, and see many opportunities for AI to enhance research capabilities, ensure diagnostic accuracy, and further automate features to reduce documentation time.

Opportunities for AI in Ultrasound Reporting

There are many opportunities for AI to positively impact ultrasound and ultrasound workflows, and help automate reporting, image analysis, and task administration — giving time back to sonographers and physicians. Some of the near-term opportunities include:

Enhancing Clinical Research Tools

Today, researchers are limited to searching text data contained in historical reports. Adding a search dimension that includes information contained in the associated historical studies and images opens many new and interesting possibilities for exploration.

Maintaining Certifications

The ability to search DICOM images by their contents can enable the creation of new features that aid in preparing submissions to maintain AIUM certifications.

Capturing Charges

By comparing the contents of images captured in a study to the procedures within an order, AI can ensure that procedures listed within an ultrasound report for billing purposes reflect the work completed. This allows organizations to capture additional charges that would otherwise be missed without AI assistance.

Improving Quality Assurance

Detecting image contents can be used to improve the efficiency of individuals performing quality assurance and quality control functions.

Approaches to AI growth and development in ultrasound

As demand for ultrasound technology innovation grows, it’s exciting to see emerging niche AI vendors like BIOTICSai and BrightHeart, and established partners like Microsoft Azure, leveraging AI to accelerate innovation throughout the industry.

There are three paths for companies like AS Software to consider when adding AI into existing solutions:

Native AI: Developing AI technologies in-house.
Acquired AI: Acquiring existing AI solutions.
Embedded AI: Integrating AI tools into existing workflows and software solutions.

While native AI development isn’t our current focus, we are actively exploring embedded and acquisition opportunities.

With an established history of embedding and complimenting electronic health records (EHR), picture archiving and communication systems (PACS), and other ultrasound and healthcare technology, AS Software is well-positioned to connect and incorporate AI tools within streamlined ultrasound workflows.

If you have any questions about the future of AI at AS Software or are interested in partnering with us to explore new ways AI can reshape ultrasound reporting, please contact us.

David Lintz is the CEO of AS Software and brings over 25 years of healthcare and technology leadership to the organization. His commitment to building strategies centered on providing value to customers, along with his visionary approach to innovation, is instrumental in propelling AS Software to offer transformative ultrasound reporting, automation, and image management solutions. Under David’s leadership, AS Software continues to expand and enhance its capabilities to better serve the healthcare market, driving efficiency for providers nationwide.