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Paper Citation Record · LEDGER

Efficient Neural Architectures for Real-Time ECG Interpretation on Limited Hardware

As of 12 August 2026, this Paper Citation Record lists 37 of 37 outbound references and 0 inbound Pith citation observations for arXiv:2605.09848.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2605.09848 v1

Coverage vector

measured 37 of 37 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-12T04:38:02.714498Z

measured 37 of 37 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

37 of 37 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation bb268cf1-75a3-44a2-bf8e-febdab6281ef · outbound

This paper cites Leading causes of death in the us, 2019-2023.

Efficient Neural Architectures for Real-Time ECG Interpretation on Limited Hardware Leading causes of death in the us, 2019-2023

Reference 1

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Observation 457ca854-9569-48b5-ab72-54497a779c18 · outbound

This paper cites The top 10 causes of death.

Efficient Neural Architectures for Real-Time ECG Interpretation on Limited Hardware The top 10 causes of death

Reference 2

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Observation 27e8876d-6642-4d77-bfa0-1ae820553bb5 · outbound

This paper cites The role of machine learning in the detection of cardiac fibrosis in electro- cardiograms: Scoping review.

Efficient Neural Architectures for Real-Time ECG Interpretation on Limited Hardware The role of machine learning in the detection of cardiac fibrosis in electro- cardiograms: Scoping review

Reference 3

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Observation b5f9896d-4e90-4a0e-845c-32b9285807f7 · outbound

This paper cites Automatic diagnosis of the 12-lead ecg using a deep neural network.

Efficient Neural Architectures for Real-Time ECG Interpretation on Limited Hardware Automatic diagnosis of the 12-lead ecg using a deep neural network

Reference 4

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Observation 95a239a8-7580-407f-937d-ba0a2fddd2e4 · outbound

This paper cites Deep learning for ecg arrhythmia detection and classification: an overview of progress for period 2017–2023.

Efficient Neural Architectures for Real-Time ECG Interpretation on Limited Hardware Deep learning for ecg arrhythmia detection and classification: an overview of progress for period 2017–2023

Reference 5

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Observation d20cf88b-0d77-4deb-968d-79ac32f9643c · outbound

This paper cites Accuracy of physicians’ elec- trocardiogram interpretations: a systematic review and meta-analysis.

Efficient Neural Architectures for Real-Time ECG Interpretation on Limited Hardware Accuracy of physicians’ elec- trocardiogram interpretations: a systematic review and meta-analysis

Reference 6

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Observation d9d1a674-126c-4489-8ef8-8d30a80e43bf · outbound

This paper cites Exploring the impact of expertise, clinical history, and visual search on electrocardiogram interpretation.

Efficient Neural Architectures for Real-Time ECG Interpretation on Limited Hardware Exploring the impact of expertise, clinical history, and visual search on electrocardiogram interpretation

Reference 7

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Source-reported events for the cited work

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Observation 8ec5346c-301d-4d32-8832-8a6cf3bac762 · outbound

This paper cites Competency in interpretation of 12-lead electrocardiogram among swiss doctors.

Efficient Neural Architectures for Real-Time ECG Interpretation on Limited Hardware Competency in interpretation of 12-lead electrocardiogram among swiss doctors

Reference 8

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Source-reported events for the cited work

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Observation 4791e068-998e-4b79-9b79-60e952535ad0 · outbound

This paper cites Accuracy of electrocardiogram interpretation by cardiologists in the setting of incorrect computer analysis.

Efficient Neural Architectures for Real-Time ECG Interpretation on Limited Hardware Accuracy of electrocardiogram interpretation by cardiologists in the setting of incorrect computer analysis

Reference 9

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Source-reported events for the cited work

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Observation b52df20e-534a-4feb-98cc-04b6d172d71b · outbound

This paper cites Ecg interpretation: clinical relevance, challenges, and advances.

Efficient Neural Architectures for Real-Time ECG Interpretation on Limited Hardware Ecg interpretation: clinical relevance, challenges, and advances

Reference 10

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Observation 4c389847-b559-459b-8b7b-fd8adaf61468 · outbound

This paper cites State-of-the-art deep learning methods on electrocardiogram data: systematic review.

Efficient Neural Architectures for Real-Time ECG Interpretation on Limited Hardware State-of-the-art deep learning methods on electrocardiogram data: systematic review

Reference 11

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Observation 6a3ef521-9c1b-43df-8897-7cfbc950a9ea · outbound

This paper cites Machine learning of electrophysiological signals for the prediction of ventric- ular arrhythmias: systematic review and examination of heterogeneity between studies.

Efficient Neural Architectures for Real-Time ECG Interpretation on Limited Hardware Machine learning of electrophysiological signals for the prediction of ventric- ular arrhythmias: systematic review and examination of heterogeneity between studies

Reference 12

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Observation 5f0a2e3e-1305-418c-97c2-5ddc87a1df5d · outbound

This paper cites Validation of an automated artificial intelligence system for 12-lead ecg interpretation.

Efficient Neural Architectures for Real-Time ECG Interpretation on Limited Hardware Validation of an automated artificial intelligence system for 12-lead ecg interpretation

Reference 13

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Observation 8da0e49e-fbc4-42ae-9d6d-88dfaa9e3ed1 · outbound

This paper cites The importance of resource awareness in artificial intelligence for healthcare.

Efficient Neural Architectures for Real-Time ECG Interpretation on Limited Hardware The importance of resource awareness in artificial intelligence for healthcare

Reference 14

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Source-reported events for the cited work

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Observation daaee479-9aa0-4d39-bde1-4a23a89740fb · outbound

This paper cites Ecg interpretation characteristics of the normal ecg (p- wave, qrs complex, st segment, t-wave).

Efficient Neural Architectures for Real-Time ECG Interpretation on Limited Hardware Ecg interpretation characteristics of the normal ecg (p- wave, qrs complex, st segment, t-wave)

Reference 15

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Observation 0c42fc2c-ee13-4e8e-a473-af558f4fe3b1 · outbound

This paper cites U-net: Convolutional networks for biomedical image segmentation.

Efficient Neural Architectures for Real-Time ECG Interpretation on Limited Hardware U-net: Convolutional networks for biomedical image segmentation

Reference 16

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Observation f2fec71b-e567-46dc-a5a4-8fac82d017f1 · outbound

This paper cites High-resolution swin transformer for automatic medical image segmentation.

Efficient Neural Architectures for Real-Time ECG Interpretation on Limited Hardware High-resolution swin transformer for automatic medical image segmentation

Reference 17

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Observation 492f41db-a0cc-40f7-b8cd-0291364c5ec5 · outbound

This paper cites Energy and policy consider- ations for modern deep learning research.

Efficient Neural Architectures for Real-Time ECG Interpretation on Limited Hardware Energy and policy consider- ations for modern deep learning research

Reference 18

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Observation e7059166-03be-4fcd-b354-5241b9d52dc9 · outbound

This paper cites Rt-rcg: Neural network and accelerator search towards effective and real-time ecg reconstruction from intracardiac electrograms.

Efficient Neural Architectures for Real-Time ECG Interpretation on Limited Hardware Rt-rcg: Neural network and accelerator search towards effective and real-time ecg reconstruction from intracardiac electrograms

Reference 19

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Observation 2cb60acc-cb6a-437f-89fa-ced8f3ac2bc8 · outbound

This paper cites Fairprune: Achieving fairness through pruning for dermatological disease diagnosis.

Efficient Neural Architectures for Real-Time ECG Interpretation on Limited Hardware Fairprune: Achieving fairness through pruning for dermatological disease diagnosis

Reference 20

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Observation 9da3f0ab-85b2-43aa-80fb-aeaf3ecf9786 · outbound

This paper cites Efficient hardware implementation of cellular neural networks with incremental quantization and early exit.

Efficient Neural Architectures for Real-Time ECG Interpretation on Limited Hardware Efficient hardware implementation of cellular neural networks with incremental quantization and early exit

Reference 21

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Observation 514a6717-efa4-479b-a0a6-7c9c1ce86fc1 · outbound

This paper cites Medq: Lossless ultra-low-bit neural network quantization for medical image segmentation.

Efficient Neural Architectures for Real-Time ECG Interpretation on Limited Hardware Medq: Lossless ultra-low-bit neural network quantization for medical image segmentation

Reference 22

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Source-reported events for the cited work

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Observation 2e26829f-6e17-489e-a7cb-e1fe007aa1c4 · outbound

This paper cites A foundational vision transformer improves diagnostic performance for electrocardiograms.

Efficient Neural Architectures for Real-Time ECG Interpretation on Limited Hardware A foundational vision transformer improves diagnostic performance for electrocardiograms

Reference 23

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Observation abb9777f-0407-4dc1-abf4-991de04536a2 · outbound

This paper cites ECG-FM: An Open Electrocardiogram Foundation Model.

Efficient Neural Architectures for Real-Time ECG Interpretation on Limited Hardware ECG-FM: An Open Electrocardiogram Foundation Model

Reference 24

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Observation fe7c5072-56fc-4e32-acf0-bb4e4f11f03c · outbound

This paper cites Convolutional neural networks for electrocardiogram classification.

Efficient Neural Architectures for Real-Time ECG Interpretation on Limited Hardware Convolutional neural networks for electrocardiogram classification

Reference 25

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Source-reported events for the cited work

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Observation 87ba6791-7023-4f2c-a9b5-f51abaaa48dd · outbound

This paper cites Screening for cardiac contractile dysfunction using an artificial intelligence–enabled electrocardiogram.

Efficient Neural Architectures for Real-Time ECG Interpretation on Limited Hardware Screening for cardiac contractile dysfunction using an artificial intelligence–enabled electrocardiogram

Reference 26

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verified fuzzy
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Source-reported events for the cited work

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Observation 4f546124-0a90-457c-a30c-cc5ae560d3e8 · outbound

This paper cites Classification of ecg using ensemble of residual cnns with attention mechanism.

Efficient Neural Architectures for Real-Time ECG Interpretation on Limited Hardware Classification of ecg using ensemble of residual cnns with attention mechanism

Reference 27

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Source-reported events for the cited work

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Observation a96cce7c-21df-4ad5-b30f-26805f693a68 · outbound

This paper cites Will two do? varying dimensions in electrocardiography: the physionet/computing in cardiology challenge 2021.

Efficient Neural Architectures for Real-Time ECG Interpretation on Limited Hardware Will two do? varying dimensions in electrocardiography: the physionet/computing in cardiology challenge 2021

Reference 28

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 7eeb0803-ba81-46ff-9808-a22797a1a48e · outbound

This paper cites Deep residual learning for image recognition.

Efficient Neural Architectures for Real-Time ECG Interpretation on Limited Hardware Deep residual learning for image recognition

Reference 29

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation aab9f267-4d62-471c-9d93-51f281fc278d · outbound

This paper cites PTB-XL, a large publicly available electrocardiography dataset (version 1.0.3).

Efficient Neural Architectures for Real-Time ECG Interpretation on Limited Hardware PTB-XL, a large publicly available electrocardiography dataset (version 1.0.3)

Reference 30

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 8a4c1588-9816-4c4b-8c65-8b9bbb5028c6 · outbound

This paper cites Ptb-xl, a large publicly available electro- cardiography dataset.

Efficient Neural Architectures for Real-Time ECG Interpretation on Limited Hardware Ptb-xl, a large publicly available electro- cardiography dataset

Reference 31

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 18e876aa-c2e3-4eec-8b89-101f3dafb42b · outbound

This paper cites A 12-lead electrocardiogram database for arrhythmia research covering more than 10,000 patients.

Efficient Neural Architectures for Real-Time ECG Interpretation on Limited Hardware A 12-lead electrocardiogram database for arrhythmia research covering more than 10,000 patients

Reference 32

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verified fuzzy
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Source-reported events for the cited work

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Observation 654c7c7b-9128-4994-ba4d-ef03ddb1db97 · outbound

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Efficient Neural Architectures for Real-Time ECG Interpretation on Limited Hardware Unresolved cited work

Reference 33

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Source-reported events for the cited work

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Observation 54bda0ff-9a29-4c6d-905b-f4ae61e1f930 · outbound

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Efficient Neural Architectures for Real-Time ECG Interpretation on Limited Hardware Unresolved cited work

Reference 34

Resolution
unresolved
raw_fallback, observed 2026-05-12T14:11:38.139269Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-12T04:38:02.714498Z digest=sha256:00f63ed1108b8f3cdf5601db404cb98b4bc6054fcf30e95e9bac05eb7017a01e

Observation 834b32b5-00cb-4e3d-bfe1-a162579f60cf · outbound

This paper cites Esc guidelines for the management of atrial fibrillation developed in collaboration with eacts.

Efficient Neural Architectures for Real-Time ECG Interpretation on Limited Hardware Esc guidelines for the management of atrial fibrillation developed in collaboration with eacts

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-05-12T14:11:38.205742Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-12T04:38:02.714498Z digest=sha256:bd5289b244e8609e85edd36525cde5a56bfa974442679680a455cc5431d529ae

Observation b5994be9-9ed3-4ebe-93f2-66e58a53e88b · outbound

This paper cites Physiobank, physiotoolkit, and physionet: components of a new research resource for complex physiologic signals.

Efficient Neural Architectures for Real-Time ECG Interpretation on Limited Hardware Physiobank, physiotoolkit, and physionet: components of a new research resource for complex physiologic signals

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-05-12T14:11:38.209107Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-12T04:38:02.714498Z digest=sha256:5f9525d45adba833e849de54e1e27e35e15c303fb0f6b6c5ccf5ca1e735c7cc8

Observation 5d5824ae-0dbd-4f3f-8718-99ae7638babb · outbound

This paper cites Mimic- iv-ecg: Diagnostic electrocardiogram matched subset.

Efficient Neural Architectures for Real-Time ECG Interpretation on Limited Hardware Mimic- iv-ecg: Diagnostic electrocardiogram matched subset

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-05-12T14:11:38.133143Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-12T04:38:02.714498Z digest=sha256:9e8c13a13898aa1e178505d369839f57ebce85df298a94ffa43296f8d4150451

Pith citing papers

No inbound Pith citation observations are available.