Pith Number

pith:F7XU7EYE

pith:2026:F7XU7EYE4TI5D6KWBBBVTWIWPD

not attested not anchored not stored refs resolved

Neural Surrogate Forward Modelling For Electrocardiology Without Explicit Intracellular Conductivity Tensor

Cesare Magnetti, Jakub Grzelak, Oleg Aslanidi, Shaheim Ogbomo-Harmitt

A neural network maps left atrial intracellular potentials to ECGs without needing explicit conductivity tensor inputs at inference time.

arxiv:2605.13366 v1 · 2026-05-13 · cs.CV · cs.LG

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\pithnumber{F7XU7EYE4TI5D6KWBBBVTWIWPD}

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4 Citations open

5 Replications open

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Claims

C1strongest claim

Despite training only on 74 subjects, the model achieved an R2 of 0.949 ± 0.037, highlighting potential to reduce structural uncertainty and improve non-invasive AF assessment.

C2weakest assumption

The learned mapping from intracellular potentials to ECGs generalizes beyond the training set and captures the underlying physics sufficiently without explicit conductivity tensors.

C3one line summary

A deep learning surrogate learns to predict ECGs from atrial potentials with R²=0.949 without requiring conductivity tensor inputs.

References

6 extracted · 6 resolved · 0 Pith anchors

[1] Forward Problem of Electrocardiography: Is It Solved? Circulation: Arrhythmia and Electrophysiology 2015

[2] Predicting Atrial Fibrillation Recurrence by Combining Population Data and Virtual Cohorts of Patient -Specific Left Atrial Models 2022

[3] In-Silico Investigation of the Right and Left Atrial Contributions to the P-Wave Morphology in ECG of Healthy and Atrial Fibrillation Patients 2024

[4] DiffusionNet: Discretization Agnostic Learning on Surfaces 2022

[5] Universal atrial coordinates applied to visualisation, registration and construction of patient specific meshes 2019

Formal links

1 machine-checked theorem link

Receipt and verification

First computed	2026-05-18T02:44:48.071780Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

2fef4f9304e4d1d1f956084359d91678c34b6498198205000d96f1f177f657cc

Aliases

arxiv: 2605.13366 · arxiv_version: 2605.13366v1 · doi: 10.48550/arxiv.2605.13366 · pith_short_12: F7XU7EYE4TI5 · pith_short_16: F7XU7EYE4TI5D6KW · pith_short_8: F7XU7EYE

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Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/F7XU7EYE4TI5D6KWBBBVTWIWPD \
  | 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: 2fef4f9304e4d1d1f956084359d91678c34b6498198205000d96f1f177f657cc

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "b6a2213f9be96447a100ae2fcd974cd256ae5e1de49ad1510e18189365bf6212",
    "cross_cats_sorted": [
      "cs.LG"
    ],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "cs.CV",
    "submitted_at": "2026-05-13T11:26:28Z",
    "title_canon_sha256": "73a105ec2e38b65ea474608a43b1d1b1a02707be5c741d260f11567fa94051f8"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2605.13366",
    "kind": "arxiv",
    "version": 1
  }
}