AI-driven platform for diagnosis, risk prediction and management of cardiac conditions

Researcher:
Dr. Joachim Behar | Biomedical Engineering

Categories:

Medical Devices

The Technology

Machine Learning (ML) driven cardiology platform that develops a cloud-based, ML-powered ECG analysis tools. It supports the diagnosis, risk prediction and management of cardiac conditions. The platform enables clinicians and technicians to perform ECG analysis faster and with better performance than current analysis software. Going beyond diagnostic support, the platform includes tools to predict the risk of developing a condition through the analysis of the raw ECG thus going beyond human visual ability in spotting early signs of deterioration, which cannot be visually appreciated by a specialist. This is thanks to the development of novel deep learning algorithms trained on thousands to millions of patients.The integrated solution provides benefits for different stakeholders. (1) Patients: early and more accurate diagnosis will provide better outcome and can reduce related comorbidities and mortality. (2) Clinicians: better diagnosis decisions and improve patient outcome with increased patient satisfaction. (3) Health care systems: reduced costs, reduced overload on hospitals and attainment of quality standards. (4) Insurance: early diagnosis of wider populations will reduce associated complications thereby reducing costs.

Advantages

  • More accurate than the state-of-the-art
  • 5-year prediction based on accurate detection of early signs of deterioration
  • Fast
  • Cloud-based

Applications and Opportunities

  • AF diagnosis
  • AF prediction and prognosis
  • AF management
  • Diagnosis and prognosis of other cardiac arrhythmias
arrow Business Development Contacts
Motti Koren
Director of Business Development, Life Sciences