Pith Number

pith:BQ6ZY7MC

pith:2026:BQ6ZY7MCL65C6MDT2D3N4QHRTE

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Extending Pretrained 10-Second ECG Foundation Models to Longer Horizons

Anshul Thakur, David A. Clifton, Fredrik K. Gustafsson, Jean-Michel Morel, Jinpei Han, Kangning Cui, Lei Clifton, Mattia Carletti, Patitapaban Palo, Raymond H. Chan, Shreyank N Gowda, Wei Tang, Xiao Gu

A lightweight plug-in module guided by a frozen 10-second ECG model can process longer and variable-length recordings without retraining the backbone.

arxiv:2605.16975 v1 · 2026-05-16 · cs.LG · cs.AI

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1 Bitcoin timestamp

2 Internet Archive

3 Author claim open · sign in to claim

4 Citations open

5 Replications open

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The bundle contains the canonical record plus signed events. A mirror can host it anywhere and recompute the same current state with the deterministic merge algorithm.

Claims

C1strongest claim

Experiments on multiple long-horizon ECG tasks, datasets, and foundation model backbones demonstrate that our method enables robust long-horizon extension from pretrained snapshot models, consistently outperforming sliding-window and pooling-based baselines with strong parameter efficiency.

C2weakest assumption

That a lightweight plug-in module guided by a frozen 10-second pretrained model can achieve semantically informed temporal aggregation for variable-length ECGs without significant loss of clinically relevant information from the original pretraining.

C3one line summary

A parameter-efficient plug-in framework adds structurally compatible long-sequence processing and semantically informed temporal modeling to extend pretrained 10-second ECG foundation models to longer variable-length inputs.

References

38 extracted · 38 resolved · 1 Pith anchors

[1] Artificial intelligence-enhanced electrocardiography in cardiovascular disease management.Nature Reviews Cardiology, 18(7):465–478, 2021 2021

[2] Deep learning for ecg analysis: Benchmarks and insights from ptb-xl.IEEE journal of biomedical and health informatics, 25(5):1519–1528, 2020 2020

[3] An electrocardiogram foundation model built on over 10 million recordings with external evaluation across multiple domains 2024

[4] Aldo Faisal, and David A 2025

[5] Ecg-fm: An open electrocardiogram foundation model.JAMIA open, 8(5):ooaf122, 2025 2025

Formal links

2 machine-checked theorem links

Receipt and verification

First computed	2026-05-20T00:03:33.955941Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

0c3d9c7d825fba2f3073d0f6de40f19938ecc4129bd6f4bdf204eb6965e10747

Aliases

arxiv: 2605.16975 · arxiv_version: 2605.16975v1 · doi: 10.48550/arxiv.2605.16975 · pith_short_12: BQ6ZY7MCL65C · pith_short_16: BQ6ZY7MCL65C6MDT · pith_short_8: BQ6ZY7MC

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Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/BQ6ZY7MCL65C6MDT2D3N4QHRTE \
  | jq -c '.canonical_record' \
  | python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: 0c3d9c7d825fba2f3073d0f6de40f19938ecc4129bd6f4bdf204eb6965e10747

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "2d0480fe1783d8014da49298543d4876e8a5cd1a58e8b7c0a75683eadf2f8b23",
    "cross_cats_sorted": [
      "cs.AI"
    ],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "cs.LG",
    "submitted_at": "2026-05-16T12:52:23Z",
    "title_canon_sha256": "8b975c971b7809caa663af3744d77e77b76dc02bd80a332f797f46435beebe5b"
  },
  "schema_version": "1.0",
  "source": {
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    "kind": "arxiv",
    "version": 1
  }
}