AISAP Study Reveals AI's Power in Single-View Cardiac Diagnostics
AISAP, a leader in AI Point-of-Care Diagnostics, has announced the publication of a groundbreaking clinical study in the peer-reviewed journal, Frontiers in Digital Health. The research provides compelling evidence that AISAP's advanced deep learning model can accurately detect significant valvular disease and ventricular dysfunction.
This detection is possible using only a single, focused ultrasound view, even when the images are acquired by non-cardiologists using handheld devices.
Breakthrough in Cardiac Screening
The study, titled "Artificial intelligence assessment of valvular disease and ventricular function by a single echocardiography view," analyzed over 120,000 echocardiographic studies during its training phase. It was subsequently validated against a prospective cohort of patients.
The model impressively demonstrated its ability to identify meaningful signatures of heart disease from standard 2D grayscale clips alone, eliminating the need for traditional and complex modalities such as color flow doppler.
The results showcased significant diagnostic performance: the AI achieved an Area Under the Curve (AUC) of up to 0.97 for detecting reduced ejection fraction and 0.95 for right ventricular dysfunction during real-world prospective testing.
Addressing Bottlenecks in Traditional Diagnostics
Lior Fisher, MD, lead author and physician at the Leviev Cardiovascular Institute at Sheba Medical Center, commented on the significance of these findings.
"These findings represent a significant shift in cardiac screening," Dr. Fisher stated, noting that proving single-view acquisition can yield high diagnostic accuracy for major pathologies effectively removes technical barriers to cardiac imaging, allowing a broader range of clinicians to identify life-threatening conditions at the point of care.
Traditional comprehensive echocardiograms typically demand a highly trained sonographer, multiple imaging angles, and expert interpretation by a cardiologist, a process that can often span days or even weeks. This new study confirms how AISAP's technology can bypass these bottlenecks, empowering frontline clinicians in various settings to provide immediate, specialist-grade triage. This capability is particularly relevant for the over-65 population, where the prevalence of valvular heart disease is highest and early detection is critical.
AISAP's Vision for Future and Current Impact
Adiel Am-Shalom, CEO and Co-Founder of AISAP, emphasized that this validation reflects AISAP's unwavering commitment to advancing AI in healthcare.
"By proving AI can rapidly extract clinically meaningful signatures from minimal ultrasound data, the study confirms the POCAD™ platform's potential for timely, bedside decision-making and immediate detection of heart disease globally."
AISAP's FDA-cleared POCAD™ platform is already being utilized in routine clinical practice to evaluate key cardiac pathologies. While this study's single-view research will inform AISAP's future innovation pipeline, its current platform remains commercially available.