What Is AI ECG Screening? Inside the Tricog CardioCheck Algorithm
Quick answer: AI ECG screening is a way of using an AI to look at an ECG and flag patients who may need a closer look within seconds. Tricog CardioCheck takes that idea and applies it to a 30-second single-lead ECG, producing a Low, Moderate or High risk assessment.
What is AI ECG screening?
Put simply, AI ECG screening uses a trained AI model to analyse an ECG at the point of capture and provide a risk assessment. The doctor still makes the clinical decision. The AI helps identify which patients may need further evaluation sooner.
That distinction matters in India, where access to timely cardiac evaluation can vary widely between healthcare settings. A 2026 European Heart Journal review puts the country at roughly 5,500 cardiologists as of 2021; about one per 30,000 people; while cardiovascular disease accounted for 29.5% of all Indian deaths in 2021, or 2.87 million people. The WHO attributes 45% of deaths in the 40–69 age group to CVD. The challenge is not simply capturing an ECG. It is getting the right clinical attention to the right ECG at the right time.
Why is single-lead ECG usually associated with rhythm monitoring?
Many single-lead ECG devices are designed primarily for rhythm monitoring, such as identifying irregular rhythms. But a single-lead ECG contains waveform information beyond heart rate alone. That makes them useful for questions about rhythm, but cardiac screening can involve a broader set of ECG features. The result is a category-wide assumption that single-lead ECG is a consumer rhythm gadget, useful for palpitations and nothing else.
Tricog CardioCheck takes a different approach, using a 30-second single-lead ECG to generate a broader cardiac risk assessment rather than focusing only on rhythm.
How does an AI ECG algorithm analyse a single-lead ECG?
TCC analyses characteristics of the ECG waveform and uses them to assign the trace to a Low, Moderate or High risk category. The idea is simple: don't look at just one part of the ECG. Look at the waveform as a whole and use the available signal to support risk assessment.
What can a single-lead ECG show?
A single-lead ECG captures electrical activity from the heart over time. That waveform can contain information about rhythm and other ECG characteristics, although a single lead cannot replace a diagnostic 12-lead ECG.
This is where AI ECG screening becomes interesting. An AI model can analyse patterns in the captured waveform consistently and provide an initial risk assessment for the clinical team.
Why does the way an AI ECG algorithm analyses the waveform matter?
An ECG waveform contains information at different levels, from individual waveform features to patterns across the recording. How an AI model processes those signals can therefore affect what it is able to identify. The challenge is separating meaningful ECG patterns from noise, movement and other sources of signal variation.
That is the entire architectural argument, and it is what allows a single lead to function as a screening instrument instead of a rhythm alert.
What does Tricog CardioCheck detect at each risk level?
TCC provides one of three risk categories, Low, Moderate or High, to help guide the next step in the clinical workflow.
High risk — Findings that may require prompt clinical evaluation, including conditions such as atrial fibrillation or myocardial infarction.
Moderate risk — ECG findings that may warrant further evaluation, such as signs associated with ischaemia or ventricular hypertrophy.
Low risk — The ECG does not show findings that trigger the higher-risk pathway. A Low-risk result does not rule out cardiac disease, so clinical judgement still matters.
Low-risk results matter too. In a busy clinic, screening is not only about finding patients who need attention. It is also about helping the clinical team organise the next step for everyone being screened.
How accurate is AI ECG screening on a single lead?
Here are the performance figures reported by Tricog from its validation data.
Reported performance
Overall discrimination: AUROC 0.909 (95% CI 0.905–0.913)
High-risk detection: 85.9% sensitivity (84.6–87.0) at 92.2% specificity (91.6–92.9)
Low-risk classification: 90.2% sensitivity (89.2–91.2)
Training data: millions of ECGs, with class imbalance corrected explicitly
Class imbalance is a common challenge when training medical AI models because some findings occur much less frequently than others. How that imbalance is handled can affect model performance.
Can an AI ECG algorithm override a cardiologist?
No. TCC is intended to support clinical triage, not replace the clinician's decision. Its risk assessment is one input into deciding whether a patient may need further evaluation.
The commercial consequence is worth saying plainly. Everything above the floor is upside — which is a rare risk profile for clinical AI.
Where does AI ECG screening fit into a clinic’s workflow?
It can sit near the front of the patient journey, alongside routine vital checks. The ECG can be captured alongside routine vitals, with the TCC risk assessment available in about ten seconds after the recording. The aim is to provide an initial risk assessment at the point of care, without requiring every ECG to wait for specialist interpretation before the next clinical step is considered.
That is the role of TCC: an AI-powered cardiac risk screening layer that can fit into the workflow where the patient is already being assessed.
Frequently asked questions
Is a single-lead ECG accurate enough for cardiac risk screening?
A single-lead ECG can be used as part of a screening and triage pathway, but it does not replace diagnostic evaluation or a 12-lead ECG when one is clinically required. Tricog CardioCheck reports AUROC 0.909 and 85.9% sensitivity for high-risk findings on a 30-second single-lead trace. It is not a substitute for a 12-lead ECG or a diagnosis.
How long does an AI ECG screening result take?
TCC provides its risk assessment in about ten seconds after the 30-second ECG recording, allowing the result to be available at the point of care.
Can AI ECG screening clear a patient as low risk?
TCC reports 90.2% sensitivity for low-risk classification in its reported validation data. A Low-risk result should not be interpreted as ruling out cardiac disease, and clinical assessment remains important. A clinician can escalate a low-risk result at any time; the model cannot de-escalate anyone.
What AI ECG screening can — and cannot — tell you
AI ECG screening is designed to support clinical triage. It is not the same thing as making a diagnosis.
A Low, Moderate or High result provides a risk assessment based on the ECG. The clinician still considers symptoms, medical history, examination and other clinical information when deciding what happens next.
When further evaluation is needed, a 12-lead ECG or other clinical assessment may be appropriate.
The interesting thing about AI ECG screening isn’t that a machine can read an ECG.
It’s what happens when that capability becomes available early in the patient journey.
A 30-second single-lead ECG can become an additional screening step. The AI provides a risk assessment. The clinical team decides what happens next.
That is where Tricog CardioCheck fits: bringing AI-powered cardiac risk screening closer to the point of care.
Sources
- Judith Ozkan, “India: challenges and opportunities for cardiologists,” European Heart Journal, Vol. 47, Issue 13, April 2026 — academic.oup.com
- World Health Organization India, Cardiovascular diseases — who.int
Bring TCC to your clinic.
Thirty seconds per patient, in the queue, before the consult.
Continue Reading
On 8 June 2025, Tricog ran its first large-scale field deployment of Tricog CardioCheck at a village clinic outside Bengaluru ...
A crowded OPD has one queue that everyone can see and another that the clinical team has to work out ...
An ECG can tell you a lot about the heart. But there is another question that matters just as much: how urgently does this ECG need attention? ...