Scaling ECG Foundation Models and Identifying a Threshold for Effective Representation Learning.

Sriram R, Nenadic I, Shahrabani E, Goonewardena SN, Yao S, Farrell B, Loring Z, Murthy VL

DOI: 10.64898/2026.07.15.26358182
Published: 2026 Jul 17
Container: medRxiv : the preprint server for health sciences
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.64898/2026.07.15.26358182,
  title = {Scaling ECG Foundation Models and Identifying a Threshold for Effective Representation Learning.},
  author = {Sriram R and Nenadic I and Shahrabani E and Goonewardena SN and Yao S and Farrell B and Loring Z and Murthy VL},
  year = {2026},
  journal = {medRxiv : the preprint server for health sciences},
  doi = {10.64898/2026.07.15.26358182},
  url = {https://doi.org/10.64898/2026.07.15.26358182}
}

RIS

TY  - JOUR
TI  - Scaling ECG Foundation Models and Identifying a Threshold for Effective Representation Learning.
AU  - Sriram R
AU  - Nenadic I
AU  - Shahrabani E
AU  - Goonewardena SN
AU  - Yao S
AU  - Farrell B
AU  - Loring Z
AU  - Murthy VL
PY  - 2026
JO  - medRxiv : the preprint server for health sciences
DO  - 10.64898/2026.07.15.26358182
UR  - https://doi.org/10.64898/2026.07.15.26358182
ER  -

APA

R, S., I, N., E, S., SN, G., S, Y., B, F., Z, L., & VL, M. (2026). Scaling ECG Foundation Models and Identifying a Threshold for Effective Representation Learning.. medRxiv : the preprint server for health sciences. https://doi.org/10.64898/2026.07.15.26358182

Source records

pubmed · retrieved 2026-09-26T09:00:09.296Z