From the 1 of 5 linked papers with an AI index.
5 papers
ELF: A Family of Encoder-Free ECG-Language Models
William Han, Tony Chen, Chaojing Duan +6
The paper introduces ELF, a family of encoder‑free ECG‑language models that interpret electrocardiograms without relying on separate pretrained ECG encoders, achieving competitive…
Retrieval-Augmented Generation for Electrocardiogram-Language Models
Xiaoyu Song, William Han, Tony Chen +4
Interest in generative Electrocardiogram-Language Models (ELMs) is growing, as they can produce textual responses conditioned on ECG signals and textual queries. Unlike traditional…
ECG-Byte: A Tokenizer for End-to-End Generative Electrocardiogram Language Modeling
William Han, Chaojing Duan, Michael A. Rosenberg +2
Large Language Models (LLMs) have demonstrated exceptional versatility across domains, including applications to electrocardiograms (ECGs). A growing body of work focuses on genera…
Signal, Image, or Symbolic: Exploring the Best Input Representation for Electrocardiogram-Language Models Through a Unified Framework
William Han, Chaojing Duan, Zhepeng Cen +7
Recent advances have increasingly applied large language models (LLMs) to electrocardiogram (ECG) interpretation, giving rise to Electrocardiogram-Language Models (ELMs). Condition…
Interpretation of Intracardiac Electrograms Through Textual Representations
William Jongwon Han, Diana Gomez, Avi Alok +5
Understanding the irregular electrical activity of atrial fibrillation (AFib) has been a key challenge in electrocardiography. For serious cases of AFib, catheter ablations are per…