Study Data Validates Implicity’s Agnostic Cloud-Based AI Algorithm in Reducing False Alerts

Study data shows Implicity’s new agnostic cloud-based artificial intelligence (AI) algorithm further reduces false alerts even after manufacturer AI filtering in modern devices.

The new data validates research presented earlier this year at the European Heart Rhythm Association (EHRA) Congress, which disclosed the reasons false-positive alerts persist in modern implantable loop recorders (ILRs). The follow-on study specifically focused on the latest AI-equipped ILRs, examining whether layering Implicity’s new, universal cloud-based AI algorithm on top of proprietary manufacturer algorithms could further reduce false alerts.

In a review of 483 cases from 324 patients using AI-equipped devices, Implicity’s next-generation ILR ECG Analyzer successfully reclassified 61.6% of false-positive alerts in interpretable episodes while maintaining 98.3% sensitivity, helping reduce the workload for clinicians without compromising patient safety.

“Manufacturer filtering has clearly advanced, whether it happens in the device, in the cloud, or through a combination of both. But even in these newer systems, residual false-positive alerts still remain and continue to burden clinical teams. The findings from our HRS study demonstrate that a manufacturer-agnostic analysis layer can substantially reduce that remaining noise while maintaining the high sensitivity needed to protect patient safety,” Implicity Co-Founder/CEO and electrophysiologist Arnaud Rosier, M.D., Ph.D., said.

Implicity’s next-generation ILR ECG Analyzer is designed to act as an agnostic second layer for residual alerts that remain after the initial manufacturer filters. Operating in the cloud and compatible with all major brands, Implicity’s new universal algorithm applies the most sophisticated neural networks, drastically reducing false positives without compromising patient safety.

This “dual AI” approach does more than just streamline remote cardiac monitoring workflows; it also reduces alert fatigue by providing clinical teams with highly accurate, trustworthy data. With greater confidence in the data, clinicians can spend less time on noise and more time focusing on meaningful cardiac events.

“Newer AI-enabled ILRs do provide a cleaner data stream with fewer obvious artifacts, but they are not perfect, and the false positives that remain are often more subtle and clinically ambiguous,” stated Niraj Varma, M.D., Ph.D., professor of Medicine and consultant electrophysiologist at the Cleveland Clinic. “Those are exactly the alerts that still require careful adjudication. In a remote monitoring workflow, that matters enormously, and any technology that can safely mitigate ILR-related false-positive alerts is significant.”

These findings follow evidence presented at EHRA examining the reasons false-positive alerts persist across modern ICM devices. In that work, investigators identified guideline-based interpretation gaps and signal-detection issues as key drivers of non-actionable alerts and determined that even in AI-equipped devices, 32.9% of episodes remained non-actionable, with another 30.6% deemed indeterminate. Together, the EHRA and HRS analyses highlight both the mechanisms behind persistent false positives and the potential for a universal, cloud-based AI approach to help address them across all devices—including those with or without proprietary AI.

Implicity’s next-generation ILR ECG Analyzer Algorithm (V2) is not cleared by the U.S. Food and Drug Administration (FDA).

Implicity is a digital medtech software company dedicated to providing the best remote care to patients with cardiac implantable electronic devices and heart failure. The platform aggregates, normalizes, and standardizes data from any implantable cardiac device across all manufacturers, improving care for patients with cardiac implants and heart failure.

Implicity’s platform provides critical health information augmented by FDA-cleared AI** algorithms, enabling healthcare providers to make more informed decisions for better patient outcomes while optimizing workflows. With access to the Health Data Hub—a gateway to one of the world’s largest databases of heart disease patients encompassing nearly the entire French cardiac patient population—Implicity develops its AI solutions based on more robust data. The company is protecting more than 110,000 patients in over 250 medical facilities across the United States and Europe.

Health Data Hub is a health data platform established by the French government to combine existing health patient databases and facilitate their usage for research and development purposes.

* The version of ILR ECG Analyzer evaluated in this study (V2) is not yet FDA cleared. Results may not be directly applicable to the currently cleared version
** SignalHF is an FDA-cleared Class II medical device, see the instructions for use for more information. IM007 ILR ECG Analyzer is an FDA-cleared Class II medical device and a CE-marked Class I (under MDD) medical device.