Key result
AI and LLM integration of heart rate variability expands, but real-world clinical validation remains lacking.
Why the study?
There is a gap between controlled studies and real clinical settings regarding the performance of AI models incorporating heart rate variability in healthcare.
Answers are grounded in this paper and cite their sources.
This narrative review highlights the challenges of data quality and uncertainty when integrating heart rate variability into AI and large language models for healthcare applications.
As global adoption of artificial intelligence (AI) continues to rise, attention has been paid to the performance of large language models (LLMs) in healthcare with emphasis on a distinct gap between the controlled studies and the real clinical settings. Heart rate variability (HRV) has emerged as an essential non-invasive tool for understanding cardiac autonomic function, evaluating and identifying various health impairments. Thus, HRV is increasingly utilized within LLMs. This narrative review comprehensively describes a range of AI-driven applications incorporating HRV based on representative cases selected from searching results. We analyse the factors' influence on data quality and the effects of performance at model output with focus on the gap between expectations and reality. The notable advances in validation technique are described. The significance of latest research on data technology is also summarized with focus on bridging the gap between clinical trust and advanced models of the next phase.
No takes yet. Share an insight, caveat, or question.
Taylor-Whilde et al. (2026) conducted a review in Cardiac autonomic function and health impairments. Heart rate variability (HRV) in artificial intelligence (AI) and large language models (LLMs) was evaluated. This narrative review highlights the increasing utilization of heart rate variability within AI and large language models, emphasizing the need to bridge the gap between controlled studies and real clinical settings.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: