Foundation for the New HRS Research Network-Foundation for the New HRS Research Network

Video Transcription

Video Summary

The session outlined a strategic vision for the Heart Rhythm Society (HRS) to elevate its research network and enhance collaboration across various projects in the field of electrophysiology (EP). Acknowledging past challenges, leaders highlighted the society's commitment to advancing research, education, and advocacy as key pillars. Emphasis was placed on forming robust networks among centers and investigators for clinical, basic, and translational research, leveraging modern tools such as artificial intelligence and comprehensive data repositories.<br /><br />Key initiatives include the HRS Research Network aimed at fostering collaborative, multi-center trials to accelerate advancements in arrhythmia research. Proposed focus areas range from sudden cardiac arrest studies to innovative technologies like conduction system pacing (CSP) and AI-driven ECG analysis. These initiatives aim to answer critical questions regarding the efficacy of new technologies, promote translational science, and ultimately improve patient care outcomes.<br /><br />The session also highlighted examples of successful models like the Canadian Heart Rhythm Society Research Network and HFSA Research Network that HRS could emulate. Additionally, the potential of large language models (LLMs) to enhance research efforts was discussed, particularly in streamlining document management, conducting systematic reviews, and integrating into multimodal data analysis.<br /><br />To support this, philanthropy and industry partnerships are viewed as crucial for funding, alongside building a sustainable endowment to back fellowships and long-term research projects. By integrating these elements, HRS aims to overcome existing barriers, promote early career development in EP research, and support diverse leadership in clinical trials.

Keywords

Heart Rhythm Society

electrophysiology

research network

collaboration

artificial intelligence

arrhythmia research

conduction system pacing

AI-driven ECG analysis

large language models

philanthropy

industry partnerships