Delivering Advanced AI to Cardiac Monitoring

The iRhythm monitoring service is bringing precision to your practice with our advanced FDA-cleared AI — the first deep-learned algorithm clinically proven to be as accurate as cardiologists.1-4

Medical staff on a computer

Enabling patient diagnosis accurately the first time5

The iRhythm monitoring service combines up to 14 days of uninterrupted ECG data6-8 with deep-learned AI1-4 that can help to reduce inaccuracies in computerized ECG interpretations and improve the efficiency of expert human ECG interpretation — accurately triaging or prioritizing the most clinically actionable conditions.2

  • Structured in layers to create an artificial neural network
  • Classifies arrhythmias at a high diagnostic performance similar to that of expert cardiologists2
  • ~8 million patient reports8
  • Over 1.5 billion hours of curated heartbeat data8
  • Detects 13 types of arrhythmia classes in this space and has been included as part of the CPT code validation process1-4

Not all AI is created equal

The iRhythm monitoring service is redefining the way cardiac arrhythmias are diagnosed by utilizing the first deep-learned algorithm clinically proven to be as accurate as cardiologists.1-4

iRhythm deep-learned artificial intelligence graph

Proven precision

The value of the iRhythm monitoring service has been demonstrated in over 100 original scientific research manuscripts.8

Clinical Article
Hannun et al., Nature Medicine, 2019.
Deep Neural Network to Detect and Classify Arrhythmias
To assess if a deep learning approach can classify a broad range of arrhythmias with diagnostic performance of cardiologists
Read more
Clinical Article
Reynolds et al, American Heart Journal, 2023.
Comparative Effectiveness of ACM Strategies (CAMELOT Study)
A retrospective study of variations in ACM strategies, clinical outcomes and health care costs in diagnostic-naïve patients
Read more
Clinical Article
Eysenck et al., Journal of Interventional Cardiac Electrophysiology, 2019.
Comparison of 4 ACMs to Permanent Pacemaker AF Detection
A prospective, randomized study to compare ACM AF burden and AF episodes in patients implanted with a pacemaker with known AF
Read more
Zio report

Advanced AI with a human touch

Recorded ECG data are processed for detection of arrhythmias using our FDA-cleared, deep-learned algorithm. The data are then curated and verified by Certified Cardiographic Technicians to generate a Zio end-of-wear report.1-4 These accurate and succinct reports8 give you data you can trust, so you can make the right diagnosis the first time.9

  • Provides comprehensive analysis based on the full wear period6,7
  • Detects 13 different types of arrhythmias, plus sinus rhythm and artifacts1-4
  • Results in 99% physician agreement10
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Full support

Questions about products, billing, or our services? We have you covered.

iRhythm offers dedicated support to help with issues like inventory management and customer satisfaction. We even have a specialized billing team to help manage revenue cycle questions and billing inquiries available 24/7/365. 

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  1. Data on file. iRhythm Technologies, 2020.
  2. Hannun et al. Cardiologist-level arrhythmia detection and classification in ambulatory electrocardiograms using a deep neural network. Nat Med. 2019;25:65-69. doi.org/10.1038/s41591-018-0268-3
  3. Deep-learned algorithm is only available in the United States, European Union, Switzerland, United Kingdom, and Japan. ​
  4. FDA 510K clearance, CE mark, and UKCA mark, and PMDA-approval.
  5. Preliminary findings in the Zio report are intended for use by clinicians as an aid in arrhythmia diagnosis and management.
  6. Zio XT Clinical Reference Manual. iRhythm Technologies, 2019.
  7. Zio monitor Instructions for Use. iRhythm Technologies, 2023.
  8. Data on file. iRhythm Technologies, 2023.
  9. Data on file. iRhythm Technologies, 2022-2023.
  10. 99% of physicians agree with the comprehensive end-of-wear report. Based on a review of all online Zio XT, Zio monitor, and Zio AT end-of-wear reports. Data on file. iRhythm Technologies, 2023.

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