Science & Technology
November 23, 2022

Idoven's AI platform, a key ally for ICMs to improve arrhythmia and false positive detection.

In recent years, the incorporation of new innovative tools in the healthcare sector has led to a revolution in the detection, treatment and control of various pathologies. We are living in a moment of technological disruption that is changing healthcare practice in hospitals and primary care centres.

Idoven was born precisely with this objective, to develop and make available to society the best technological innovation to transform the way in which cardiac diagnosis and care is offered thanks to the creation of different tools and services based on AI. To achieve this, we consider research, knowledge and experience sharing between the different actors in the healthcare ecosystem to be essential. In this way, sooner rather than later, we will have a real impact in the fight against the world's leading cause of death: cardiovascular disease.

Thanks to this spirit of collaboration, we can announce that we have worked together with Abbott to analyze the outcome of implementing our AI-based software to improve the accuracy of their ICM devices used for arrhythmia diagnosis.

What are the main results of this collaboration?

According to the research, led by Abbott, the Hospital of Reggio Emilia, and Idoven, and in collaboration with the Centro Nacional de Investigaciones Cardiovasculares (CNIC), the Centro Español de Red de Investigación Biomédica en Enfermedades Cardiovasculares (CIBERCV), and the Interhospital Foundation for Cardiovascular Research (FIC), it shows that the use of AI potentially improves the operability of continuous monitoring devices and facilitates diagnosis for healthcare professionals.

Data from this research shows that the application of AI software improved ICM accuracy by 95.4% for arrhythmia detection and reduced false positive detections by 98%, as published in the Cardiovascular Digital Health Journal.

Results of the study

In particular, the AI algorithm identified 187/199 AT/AF false positives (false positive reduction equal to 94.0%),  7/8 VT false positives (false positive reduction equal to 87.5%), 186/187 brady false positives (false positive reduction equal to 99.5%) and 685/693 asystole false positives (false positive reduction equal to 98.8%).

False positive detections after AI application by episode type

How was the study conducted?

Abbott’s ICM Confirm RxTM was used for this study. Their use has increased in recent years due to the development of smaller, more sophisticated devices and the emergence of new clinical indications recommending their use for monitoring patients with unexplained syncope or at risk of cardiac arrhythmias. This continuous monitoring still produces a large volume of ECGs that must nowadays be manually reviewed by cardiologists to identify relevant cardiovascular problems and risks.

Automated classification and review of ICM episodes by AI

Thus, the study has proven how the application of the software developed by Idoven allows the detection of arrhythmias to be much more accurate and false positives practically disappear. In this way, and thanks to AI, Idoven has developed software capable of interpreting electrocardiogram data with almost perfect accuracy. This makes it a new tool to help doctors in their consultations, reducing their workload and improving diagnostic accuracy. 

Undoubtedly, this is another example of how, thanks to studies like this one, the potential of Artificial Intelligence developed by Idoven can help healthcare professionals in their care work and how this has a direct impact on the care offered to patients, who can have a much more accurate diagnosis and, therefore, be treated more precisely.

If you are interested in learning more about this study, find the full paper here:

Jose María Lillo Castellano
CSO & Co-Founder at

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