๐Ÿ›๏ธ Verified NIH Record โ€ข Updated 2025-11-12

Machine Learning in Atrial Fibrillation (NCT05371405)

๐ŸŸข Recruiting Interventional Protocol ๐Ÿ“Š Observational Clinical Research Sponsor: Stanford University

๐Ÿฉบ Plain-English Summary (8th-Grade Level)

Atrial fibrillation is a serious public health issue that affects over 5 million Americans (Miyazaka, Circulation 2006) in whom it may cause skipped beats, dizziness, stroke and even death. Therapy for AF is currently suboptimal, in part because AF represents several disease states of which few have been delineated or used to successfully guide management. This study seeks to clarify this delineation of AF types using machine learning (ML).

Who can join: Review the eligibility criteria below.

Location: Stanford University โ€” Stanford, California

Age range: 22 Years to 80 Years

๐Ÿ“‹ "Do I Qualify?" โ€” 1-Minute Self Screener

Instant Checklist

Full eligibility criteria are available on the official NIH protocol. View the criteria โ†—

๐Ÿ“ All Participating Trial Locations (1 Sites)

  • Stanford University โ€” Stanford, California

๐Ÿ“ž Contact the Study Coordinator

Phone: (650) 724-1850

Email: sanjiv1@stanford.edu

Coordinator details come directly from the registered NIH protocol. Confirm the study is still recruiting before traveling.

๐Ÿ’ฐ Cost, Insurance & Patient Rights

  • 100% Free Items: The investigational treatment and protocol-required procedures are supplied at zero cost by the sponsor.
  • Routine Patient Care: Under federal law (ACA ยง 2709) and many state statutes, routine care costs are covered during participation.
  • Voluntary Participation: You may withdraw at any time without affecting your standard medical care.

๐Ÿ’ก How to Participate

  1. Check the checklist above to see if you may qualify.
  2. Contact the study coordinator using the phone/email above.
  3. Ask about the visit schedule, what is covered at no cost, and any travel support.
  4. Confirm with your own doctor before making a decision.
๐Ÿ›๏ธ View Official NIH Record โ†—