Cardiology’s AI Moment: Anumana’s Top Insights from ACC.25

#TeamAnumana wrapped up three incredible days of exploring cardiovascular science in the Windy City at the American College of Cardiology’s Annual Scientific Session. ACC.25 brought together thousands of cardiologists, investigators, and innovators under one roof, all exploring the future of cardiovascular care.

Thank you to everyone who visited Anumana’s booth and attended our reception to meet our team, learn about our FDA-cleared ECG-AI™ LEF Software as a Medical Device, experience a demo, or discuss next steps in bringing AI-driven insights to patient care!

"Is AI Replacing Cardiologists?"

A recurring theme at ACC.25 was the question: "Will AI replace cardiologists?" The consensus: AI isn’t replacing cardiologists, but those who integrate AI will outperform those who don’t.  

Dr. Ami Bhatt, Chief Innovation Officer at the ACC, emphasized that AI is a necessity for clinicians, not a replacement for their expertise, pointing out that:

> AI enables earlier identification of undiagnosed patients through clinician decision support tools
> AI-powered clinical decision support enhances efficiency, allowing clinicians to manage more patients effectively
> AI can optimize treatment at scale while reducing workload, freeing up time for complex patient care
> Lessons from radiology suggest AI can improve workflows, helping clinicians focus on what they were trained to do

Today, to treat more patients, clinicians relying on AI is a matter of “when”, not “if”.  

Dr. John S. Rumsfeld, Director of Health Technology Research at Reality Labs (Meta) and Professor of Medicine at the University of Colorado, reinforced this in his talk on the past, present, and future of AI in cardiovascular medicine. His key advice? Clinicians don’t need to be coding experts but should be critical consumers of AI.

Workflow Integration is Key 

Several sessions at ACC.25 emphasized the importance of AI solutions integrating seamlessly into clinical workflows. Discussions around ambient listening and AI-driven note-taking showcased how technology is already streamlining documentation, disease detection, clinical decision support, and imaging interpretation. 

A common trend among applications of AI is the need for the solutions to integrate or improve the clinical workflow and patient journey rather than disrupt it.

Dr. Hilary DuBrock, Associate Professor of Medicine and Pulmonary Hypertension Fellowship Program Director at Mayo Clinic, illustrated how AI could significantly improve the diagnostic journey for pulmonary hypertension (PH). Since PH often presents with non-specific symptoms, many patients endure years of tests before a diagnosis.  

Similarly, Anumana’s ECG-AI™ LEF algorithm for earlier identification for low ejection fraction can transform patient care by providing clinicians with an opportunity to intervene earlier. Since our algorithm is also designed to fit into the clinician’s existing workflow, LEF can directly enhance early detection and improve patient care where it’s most impactful.  

Fit-for-Purpose AI Solutions 

Speakers at ACC.25 emphasized that AI tools for population-based screening should be: 

> Non-invasive
> Widely accessible
> Low-cost

By contrast, AI solutions designed for more advanced diagnostics or disease monitoring may require specialized, costly, or invasive inputs for optimal performance.

Anumana’s ECG-AI LEF algorithm, which detects low left ventricular ejection fraction (LEF) from a standard 12-lead ECG, exemplifies how AI can be used effectively for broad screening. ECGs are inexpensive, non-invasive, and widely available, making them ideal for early detection*.

Looking Ahead 

ACC.25 provided an exciting glimpse into the future of AI in cardiology. The enthusiasm from investigators and innovators leveraging ECG data for AI-driven solutions was inspiring.

If you didn’t get the chance to meet with our team and want to learn more about ECG-AI™ and how it can transform your practice, schedule a meeting with us today!

As AI continues to enhance cardiovascular care, #TeamAnumana looks forward to seeing what’s next—including more advancements at ACC.26! 



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*The Anumana Low Ejection Fraction AI-ECG Algorithm is software intended to aid in screening for Low Ventricular Ejection Fraction (LVEF) less than or equal to 40% in adults (aged 18 and above) at risk for heart failure. This population includes, but is not limited to:

> patients with cardiomyopathies
> patients who are post-myocardial infarction
> patients with aortic stenosis
> patients with chronic atrial fibrillation
> patients receiving pharmaceutical therapies that are cardiotoxic, and
> postpartum women

Anumana Low Ejection Fraction AI-ECG Algorithm is not intended to be a stand-alone diagnostic device for cardiac conditions, should not be used for monitoring of patients, and should not be used on ECGs with a paced rhythm.

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