Abstract
Identifying patients at high-risk of sudden cardiac death (SCD) in the mid to long-term remains particularly challenging. Accurate prediction of lethal ventricular arrhythmias in the near-term would enable preemptive actions to eventually prevent SCD. We hypothesized that artificial intelligence could be leveraged to identify a dynamic electrical profile on Holter ECG data heralding the near-term occurrence of sustained ventricular tachycardia (VT).
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
