Published in the International Journal of Cardiology, new study demonstrates 91.6% accuracy and introduces the HF-index for on-demand severity tracking

 Simplex Quantum, in collaboration with the University of Tokyo Hospital, announced the publication of a clinical study in the International Journal of Cardiology. The peer-reviewed research introduces a novel artificial intelligence system capable of accurately assessing heart failure (HF) severity and tracking disease progression using single-lead ECG data from commonly available devices, including the Apple Watch.

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At the core of this breakthrough is the HF-index, a new AI-derived metric that enables on-demand monitoring of heart failure severity from home. This technology has a significant potential to reduce hospitalizations by enabling earlier clinical intervention.

Key Findings

  • The AI model, trained on ECG data from 9,518 individuals, achieved 91.6% accuracy in classifying heart failure severity across healthy, NYHA I–II (mild), and NYHA III–IV (moderate to severe) categories.
  • The model demonstrated AUC values up to 0.993, with sensitivity and specificity between 89–97%.
  • The HF-index showed a strong correlation with plasma B-type Natriuretic Peptide (BNP) levels (R = 0.74), a widely accepted biomarker for heart failure.

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Expert Commentary

“This AI model may support on-demand, non-invasive heart failure monitoring, even before symptoms appear,” said Dr. Katsuhito Fujiu, Project Professor at the University of Tokyo and senior author of the study. “It could fundamentally change how we care for patients at risk of worsening heart failure by empowering both clinicians and patients with timely insights.”

“These results validate the clinical foundation of our solution and show how AI can turn familiar devices into powerful medical tools,” said Ryu Saito, CEO of Simplex Quantum. “We are proud to collaborate with top-tier institutions to bring this technology into everyday practice.”

Why This Matters

Heart failure affects over 64 million people globally and is a leading cause of hospital readmissions and rising healthcare costs. Existing monitoring options, such as implantable devices or in-hospital diagnostics, can be invasive, expensive, or unavailable to many patients. This AI-powered solution could provide a scalable, at-home alternative using devices already in wide consumer use.

About the Study

  • Title: Heart Failure Monitoring with a Single-Lead Electrocardiogram at Home
  • Journal: International Journal of Cardiology
  • DOI: 10.1016/j.ijcard.2025.133203

Regulatory and Commercialization Path

The AI system described in the study powers NIHA-HF, Simplex Quantum’s investigational software platform for heart failure risk detection and monitoring. Regulatory submissions are currently underway in Japan and the United States, with product approvals targeted for 2026.

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Source – PR Newswire