Earlier high-risk detection
Identify high-risk patients sooner so care teams can intervene earlier.
Transform the first ECG into a real-time decision tool
ECG-SMART for Real-Time Cardiac Triage
IntelliCardio delivers instant, AI-driven ECG analysis to help clinicians identify high-risk patients earlier, safely rule out low-risk cases, and reduce unnecessary hospital admissions at the point of care.
Confident low-risk discharge
Support safe rule-out decisions and reduce unnecessary admissions.
Operational efficiency
Improve patient flow with faster, more actionable cardiac risk assessment.
The problem
Cardiac diagnosis is time-critical, but current workflows are not.
More than 40 million patients receive ECG evaluation in emergency departments each year. Today, clinicians often rely on serial biomarkers, repeat ECGs, and risk scores—processes that can require hours of observation before a confident decision is made.
During this critical window, high-risk patients may go undetected, while low-risk patients are admitted for unnecessary testing. Using only the initial ECG, IntelliCardio is designed to shift cardiac triage from reactive observation to proactive, real-time decision-making.
See the workflowThe solution
Real-time cardiac risk stratification at first medical contact.
For hospitals
ECG-SMART decision engine
Transform the ECG from a screening tool into a real-time decision engine that provides actionable risk stratification within minutes, not hours.
01
Instant ECG analysis
Analyze ECG signals at acquisition to support earlier detection of life-threatening cardiac conditions and more confident triage.
02
Enterprise integration
Integrate with leading ECG management systems, including GE MUSE, Philips IntelliVue, and Zoll, without requiring new hardware.
03
Scalable condition coverage
Initially focused on occlusive myocardial infarction, with a platform roadmap spanning ACS, pulmonary embolism, and early or subclinical atrial fibrillation.
How it works
Seamless integration into clinical workflows.
IntelliCardio operates in the background of existing ECG infrastructure. A standard 12-lead ECG is acquired as usual, analyzed in real time, and translated into a clear, interpretable risk assessment for the clinical team.
1
Acquire standard ECG
Use the same 12-lead ECG workflow already present at patient presentation.
2
Analyze in real time
Process the ECG signal instantly through IntelliCardio's AI engine.
3
Deliver risk assessment
Return interpretable outputs through a web dashboard, alerts, or notifications.
4
Guide next steps
Support immediate intervention, targeted admission, or safe discharge decisions.
Technology and integration
Enterprise-ready, scalable, and secure.
IntelliCardio is designed for real-world hospital deployment at scale, operating securely behind the hospital firewall and aligning with institutional data governance and cybersecurity requirements**.
ECG system connectivity
Built to integrate with GE MUSE, Philips IntelliVue, Zoll, and related ECG workflows.
Flexible clinical delivery
Provide results through a web-based dashboard, automated alerts, or mobile notifications.
No workflow disruption
Deploy without additional hardware or changes to how clinical teams acquire ECGs.
Scientific foundation
Built on rigorous science and clinical validation.
IntelliCardio is grounded in over a decade of translational research across cardiology, engineering, and clinical informatics, supported by peer-reviewed publications, NIH funding, multi-site datasets, and issued U.S. patents.
Article - European Heart Journal - Digital Health
Novel Machine Learning Fusion Architectures Integrating Electrocardiogram Representations: Applications to Acute Coronary Event Detection
ReadArticle - IEEE Transactions on Biomedical Engineering
ECG-SMART-NET: A Deep Learning Architecture for Precise ECG Diagnosis of Occlusion Myocardial Infarction
ReadArticle - European Heart Journal - Digital Health
Artificial intelligence-driven electrocardiogram analysis for risk stratification in pulmonary embolism
ReadArticle - Nature Medicine
Machine learning for ECG diagnosis and risk stratification of occlusion myocardial infarction
ReadArticle - Nature Communications
Machine learning-based prediction of acute coronary syndrome using only the pre-hospital 12-lead electrocardiogram
ReadArticle - European Heart Journal
Electrocardiogram-based machine learning for risk stratification of patients with suspected acute coronary syndrome
ReadArticle - Journal of Electrocardiology
Clinical usability of deep learning-based saliency maps for occlusion myocardial infarction identification from the prehospital 12-Lead electrocardiogram
ReadArticle - Journal of Electrocardiology
Novel ECG features and machine learning to optimize culprit lesion detection in patients with suspected acute coronary syndrome
ReadArticle - Annals of Emergency Medicine
Incorporation of Serial 12-Lead Electrocardiogram With Machine Learning to Augment the Out-of-Hospital Diagnosis of Non-ST Elevation Acute Coronary Syndrome
ReadAbstract - European Society of Cardiology
External validation of the ECG-SMART model: a machine learning algorithm for ECG diagnosis of occlusion myocardial infarction
ReadAbstract - American Heart Association (AHA) Scientific Sessions
External Validation of an AI-ECG algorithm for Occlusive Myocardial Infarction Detection in a General Chest Pain Population
ReadAbout us
World-class leadership in cardiology, AI, and emergency medicine.
IntelliCardio is led by a multidisciplinary team translating advanced AI, cardiovascular science, and clinical research into real-world healthcare impact.
Founders
Salah Al-Zaiti, PhD
Chief Executive Officer
Endowed Professor and clinician-scientist with 15+ years in cardiovascular AI. NIH-funded investigator ($7M+), published in Nature Medicine. Editor-in-Chief of Heart & Lung and Vice President of ISCE. Leads translational innovation at the intersection of cardiology, engineering, and real-world clinical deployment.
Salah Al-Zaiti, PhD
Chief Executive Officer
Clifton Callaway, MD, PhD
Chief Medical Officer
Distinguished Professor and emergency physician with 25+ years of clinical and research leadership. NIH-funded investigator ($32M+), contributor to AHA guidelines, and widely cited scholar (H-index 115). Expert in emergency cardiovascular care and translating research into practice.
Clifton Callaway, MD, PhD
Chief Medical Officer
Ervin Sejdić, PhD
Chief Technology Officer
Endowed Professor and Research Chair in AI with expertise in biomedical signal analytics. NIH/NSF-funded investigator ($8M+), Editor-in-Chief of Biomedical Engineering Online, and inventor with 8 patents. Experienced entrepreneur driving translation of AI innovations into healthcare solutions.
Ervin Sejdić, PhD
Chief Technology Officer
Murat Akcakaya, PhD
Chief AI Officer
Associate Professor and machine learning expert specializing in biomedical signal processing. NSF and DoD-funded investigator ($16M+), Senior IEEE member. Develops advanced AI algorithms for physiological data with applications in real-time clinical decision support.
Murat Akcakaya, PhD
Chief AI Officer
Advisors and Team Members
Jean-Philippe Couderc, PhD, MBA
Professor and biomedical engineer with global expertise in quantitative electrocardiography and AI-driven cardiac analytics. Founder of multiple successful startups and currently leading VPG Medical. Extensive track record in translating ECG innovation into clinical and commercial applications across academia and industry.
Jean-Philippe Couderc, PhD, MBA
Fabio Badilini, PhD, FACC
Internationally recognized expert in quantitative electrocardiography and cardiovascular signal processing. Founder of AMPS LLC and contributor to FDA ECG data standards used globally in cardiac safety studies. Leads innovations in advanced ECG analytics, digital biomarkers, and translational biosignal research.
Fabio Badilini, PhD, FACC
Brian Young, MS
Industry leader with 30+ years in ECG technology and cardiovascular diagnostics. Holds 30+ patents and has led development of global ECG standards (ISO) and FDA regulatory strategies. Former GE Healthcare executive with deep expertise in translating advanced ECG analytics into scalable and commercial clinical products.
Brian Young, MS
Emir Muhović
Healthcare investor and operator with expertise in scaling digital health and AI-driven companies. Partner at a leading healthcare venture firm, with a track record of advising and investing in high-growth medtech and software startups. Brings deep experience in strategy, fundraising, and commercialization.
Emir Muhović
Howard Palefsky
Experienced healthcare executive and strategic advisor with a track record of building and scaling high-growth healthcare and digital health companies. Former CEO and board leader with deep expertise in commercialization, operations, and go-to-market strategy. Advises startups on growth, fundraising, and execution.
Howard Palefsky
Nathan Riek, PhD
Machine learning engineer and biomedical AI scientist specializing in ECG analytics and cardiovascular risk prediction. Developer of ECG-SMART-NET and contributor to multiple high-impact AI-ECG studies published in Nature Medicine and IEEE journals. Expertise spans deep learning, explainable AI, and real-time clinical decision support.
Nathan Riek, PhD
Rui Qi Ji, PhD(c)
AI researcher and biomedical engineer specializing in machine learning for ECG analytics and cardiovascular risk prediction. Contributor to ECG-SMART and multiple AI-ECG studies focused on occlusive myocardial infarction, fairness in AI, and clinician-centered decision support systems.
Rui Qi Ji, PhD(c)
Gazihan Alankuş, PhD
Professor in computer science and full-stack software developer specializing in clinical AI platforms and healthcare interfaces. Leads development of IntelliCardio’s real-time ECG analytics infrastructure, including cloud deployment, explainable AI visualization, and seamless integration into hospital clinical workflows.
Gazihan Alankuş, PhD
Tanmay Gokhale, MD, PhD
Cardiac electrophysiologist and physician-scientist working at the intersection of AI and cardiovascular medicine. Leads development of advanced AI-ECG models for pulmonary embolism and acute cardiac risk prediction. Expertise spans computational cardiology, explainable AI, and translational clinical deployment.
Tanmay Gokhale, MD, PhD
Samir Saba, MD
Chief of Cardiology and Co-Director of the UPMC Heart & Vascular Institute. Internationally recognized cardiac electrophysiologist with expertise in arrhythmias, implantable cardiac devices, and translational cardiovascular research. NIH-funded investigator with 250+ publications, multiple patents, and leadership roles in major cardiology journals and societies.
Samir Saba, MD
Peter van Dam, PhD
Biomedical engineer and internationally recognized expert in inverse electrocardiography and cardiac modeling. Founder and CSO of ECG Excellence, inventor with 15+ patents, and former Medtronic scientist. Pioneer of CineECG technology with extensive experience translating advanced ECG analytics into clinically deployable cardiovascular solutions
Peter van Dam, PhD
Karina Kraevsky, PhD
Clinician-scientist and biomedical AI researcher focused on cardiovascular physiology, ECG analytics, and data-driven modeling of cardiac risk. Contributor to AI-enabled ECG research and translational clinical studies at the intersection of machine learning, emergency care, and cardiovascular outcomes research.
Karina Kraevsky, PhD
Market opportunity
A software platform for a large and growing cardiac diagnostics market.
IntelliCardio operates at the intersection of ECG diagnostics, cardiac monitoring, and artificial intelligence. The global ECG diagnostics market is valued at over $9 billion, with the broader cardiac monitoring market exceeding $20 billion.
Unlike device-focused or narrow point solutions, IntelliCardio is positioned as a comprehensive software-driven platform that can expand across multiple cardiovascular risk detection use cases.
FAQ
Questions hospitals usually ask first.
What is ECG-SMART?
ECG-SMART is a software that runs within your hospital firewalls in parallel with your own ECG management system to deliver real-time AI-powered evaluation of the ECG to clinicians at the point-of-care.
Does it replace clinicians?
No. IntelliCardio supports clinician-led decisions by surfacing ECG insights, risk stratification, and explanation context. Clinicians remain responsible for diagnosis and treatment decisions.
How is data privacy handled?
IntelliCardio is designed to operate securely behind the hospital firewall, aligning with institutional data governance and cybersecurity requirements.
Which conditions can the platform support?
IntelliCardio is initially focused on occlusive myocardial infarction and is built as a scalable ECG platform for additional conditions including ACS, pulmonary embolism, and early or subclinical atrial fibrillation.
Product demo
See the ECG-SMART dashboard in context.
Designed for clear clinical review
Contact usMedia Coverage
Latest updates.
T.H.I.N.K Conference 2025
Our CEO, Dr. Salah Al-Zaiti, sharing our work at the T.H.I.N.K Conference, Stanford Faculty Club, Palo Alto, CA
Read moreFuturum Careers
Can artificial intelligence detect hidden heart attacks?
Read moreNews Medical
News featuring our work in Nature Medicine: Improved diagnosis of occlusion myocardial infarction using novel machine learning tools
Read moreWTAE
University of Pittsburgh researchers and UPMC are studying AI to detect heart attacks faster
Read moreMedical Xpress
New AI tool beats standard approaches for detecting heart attacks
Read moreMayo Clinic
Emerging ECG Methods for Ischemia Detection
Read morePittwire
New AI Research Looks to Better Diagnose Heart Attacks Before Hospital Arrival
Read moreOur Partners
Built alongside leaders in cardiovascular innovation.
Our ECG-SMART technology has been validated in a cohort of over 20,000 patients across multiple sites in the U.S. and Europe.
Contact
Join us in transforming cardiac care.
We are working with leading clinical partners to evaluate real-time AI-powered cardiac triage for future clinical use and FDA clearance. Health system leaders, clinicians, and investors are invited to collaborate.