Modeling Day-Long ECG Signals to Predict Heart Failure Risk with Explainable AI | Paper Citation Record

Observation 02efbc5a-a156-4631-a9fd-dc1d253f5d52 · outbound

This paper cites European Journal of Heart Failure22(8), 1342–1356 (2020) https://doi.org/10.1002/ejhf.1858.

Modeling Day-Long ECG Signals to Predict Heart Failure Risk with Explainable AI European Journal of Heart Failure22(8), 1342–1356 (2020) https://doi.org/10.1002/ejhf.1858

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-03T15:01:39.084602Z

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Observation 3218f2f2-6df3-4804-b580-bd8bb07e883b · outbound

This paper cites The Lancet393(10175), 1034–1044 (2019) https://doi.org/10.1016/S0140-6736(18)31808-7.

Modeling Day-Long ECG Signals to Predict Heart Failure Risk with Explainable AI The Lancet393(10175), 1034–1044 (2019) https://doi.org/10.1016/S0140-6736(18)31808-7

Reference 2

Resolution: verified exact; doi, observed 2026-08-03T15:04:08.205677Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation f3e699c7-b72b-4f93-ad5c-79500c7d7804 · outbound

This paper cites Circulation145(18), 895–1032 (2022) https://doi.org/10.1161/CIR.0000000000001063.

Modeling Day-Long ECG Signals to Predict Heart Failure Risk with Explainable AI Circulation145(18), 895–1032 (2022) https://doi.org/10.1161/CIR.0000000000001063

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-03T15:01:39.385801Z

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Observation 8cb704e7-e5b2-4b9e-b67a-235568ba3af9 · outbound

This paper cites Heart & Lung31(4), 262–270 (2002) https://doi.org/10.1067/mhl.2002.

Modeling Day-Long ECG Signals to Predict Heart Failure Risk with Explainable AI Heart & Lung31(4), 262–270 (2002) https://doi.org/10.1067/mhl.2002

Reference 4

Resolution: verified exact; doi, observed 2026-08-03T15:04:07.958714Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 6d6d3953-2d11-46b5-8fc9-cc56f257ff95 · outbound

This paper cites Journal of Cardiac Failure27(4), 387–413 (2021) https://doi.org/10.1016/J.CARDF AIL.2021.01.022.

Modeling Day-Long ECG Signals to Predict Heart Failure Risk with Explainable AI Journal of Cardiac Failure27(4), 387–413 (2021) https://doi.org/10.1016/J.CARDF AIL.2021.01.022

Reference 5

Resolution: malformed identifier; no resolver link, observed 2026-08-03T15:01:39.697118Z

Source-reported events for the cited work

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Observation 31e40f64-3ebe-41a1-9bb9-aa0583405892 · outbound

This paper cites Circulation135(10), 146–603 (2017) https://doi.org/10.1161/CIR.0000000000000485/ ASSET/065F105B-352E-48D3-AC2B-2F0A69AE4BE0/ASSETS/CIR.0000000000000485.FP.PNG.

Modeling Day-Long ECG Signals to Predict Heart Failure Risk with Explainable AI Circulation135(10), 146–603 (2017) https://doi.org/10.1161/CIR.0000000000000485/ ASSET/065F105B-352E-48D3-AC2B-2F0A69AE4BE0/ASSETS/CIR.0000000000000485.FP.PNG

Reference 6

Resolution: malformed identifier; no resolver link, observed 2026-08-03T15:01:39.878786Z

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Observation 56a579dd-df07-4649-9ead-e8dda40282b0 · outbound

This paper cites European Heart Journal44(Supplement 2), 655–892 (2023) https://doi.org/10.1093/eurheartj/ehad655.892.

Modeling Day-Long ECG Signals to Predict Heart Failure Risk with Explainable AI European Heart Journal44(Supplement 2), 655–892 (2023) https://doi.org/10.1093/eurheartj/ehad655.892

Reference 7

Resolution: verified exact; doi, observed 2026-08-03T15:04:07.782808Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 7cc48c6c-fe2c-422f-b4e6-a2ba30bae375 · outbound

This paper cites Nature Communications11(1), 1760–1760 (2020) https://doi.org/10.1038/ s41467-020-15432-4.

Modeling Day-Long ECG Signals to Predict Heart Failure Risk with Explainable AI Nature Communications11(1), 1760–1760 (2020) https://doi.org/10.1038/ s41467-020-15432-4

Reference 8

Resolution: malformed identifier; no resolver link, observed 2026-08-03T15:01:40.288054Z

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Observation 0fb11708-e218-4611-9077-c90d13c85fff · outbound

This paper cites European Heart Journal - Digital Health2(4), 576–585 (2021) https://doi.org/10.1093/EHJDH/ZTAB071 14.

Modeling Day-Long ECG Signals to Predict Heart Failure Risk with Explainable AI European Heart Journal - Digital Health2(4), 576–585 (2021) https://doi.org/10.1093/EHJDH/ZTAB071 14

Reference 9

Resolution: verified exact; doi, observed 2026-08-03T15:04:07.585099Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation fd6d6514-7103-43cf-bbdb-c25831f28080 · outbound

This paper cites Nature Medicine29, 1804–1813 (2023) https://doi.org/10.1038/s41591-023-02396-3.

Modeling Day-Long ECG Signals to Predict Heart Failure Risk with Explainable AI Nature Medicine29, 1804–1813 (2023) https://doi.org/10.1038/s41591-023-02396-3

Reference 10

Resolution: verified exact; doi, observed 2026-08-03T15:04:07.372008Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 0f9c62cb-8078-4f72-b825-ed49e4805eb0 · outbound

This paper cites Communications Medicine3, 73–73 (2023) https://doi.org/10.1038/ s43856-023-00278-w.

Modeling Day-Long ECG Signals to Predict Heart Failure Risk with Explainable AI Communications Medicine3, 73–73 (2023) https://doi.org/10.1038/ s43856-023-00278-w

Reference 11

Resolution: malformed identifier; no resolver link, observed 2026-08-03T15:01:40.835605Z

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Observation 98a615c9-8760-47b2-9975-2b284ca63595 · outbound

This paper cites Nature Medicine25(1), 70–74 (2019) https://doi.org/10.1038/s41591-018-0240-2.

Modeling Day-Long ECG Signals to Predict Heart Failure Risk with Explainable AI Nature Medicine25(1), 70–74 (2019) https://doi.org/10.1038/s41591-018-0240-2

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-03T15:01:40.953653Z

Source-reported events for the cited work

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Observation b1f89638-2d12-42ae-b76d-8394810f4790 · outbound

This paper cites Journal of Cardiovascular Electrophysiology30(5), 668–674 (2019) https: //doi.org/10.1111/JCE.13889.

Modeling Day-Long ECG Signals to Predict Heart Failure Risk with Explainable AI Journal of Cardiovascular Electrophysiology30(5), 668–674 (2019) https: //doi.org/10.1111/JCE.13889

Reference 13

Resolution: verified exact; doi, observed 2026-08-03T15:04:07.149248Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 70cc7aee-1eb3-4b49-92d9-8af1e30e917a · outbound

This paper cites Nature Reviews Cardiology14(10), 591–602 (2017) https://doi.org/10.1038/nrcardio.2017.65.

Modeling Day-Long ECG Signals to Predict Heart Failure Risk with Explainable AI Nature Reviews Cardiology14(10), 591–602 (2017) https://doi.org/10.1038/nrcardio.2017.65

Reference 14

Resolution: verified exact; doi, observed 2026-08-03T15:04:06.957675Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation e97ef332-66e2-4506-a6f3-416754fa1054 · outbound

This paper cites Nature Reviews Cardiology21(10), 717–734 (2024) https://doi.org/10.1038/s41569-024-01046-6.

Modeling Day-Long ECG Signals to Predict Heart Failure Risk with Explainable AI Nature Reviews Cardiology21(10), 717–734 (2024) https://doi.org/10.1038/s41569-024-01046-6

Reference 15

Resolution: verified exact; doi, observed 2026-08-03T15:04:06.760640Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 414345a5-a47e-494e-b25b-4c4b1ccf21c2 · outbound

This paper cites European Heart Journal43(20), 1917–1927 (2022) https://doi.org/10.1093/ eurheartj/ehac088.

Modeling Day-Long ECG Signals to Predict Heart Failure Risk with Explainable AI European Heart Journal43(20), 1917–1927 (2022) https://doi.org/10.1093/ eurheartj/ehac088

Reference 16

Resolution: malformed identifier; no resolver link, observed 2026-08-03T15:01:41.540797Z

Source-reported events for the cited work

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Observation c2bfa008-89f3-4fde-aafd-bf6612f0ccb6 · outbound

This paper cites Journal of the American College of Cardiology73(19), 2388–2397 (2019) https://doi.org/10.

Modeling Day-Long ECG Signals to Predict Heart Failure Risk with Explainable AI Journal of the American College of Cardiology73(19), 2388–2397 (2019) https://doi.org/10

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-03T15:01:41.655563Z

Source-reported events for the cited work

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Observation ddc0529a-d198-4800-a9fe-24b356216db8 · outbound

This paper cites In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pp.

Modeling Day-Long ECG Signals to Predict Heart Failure Risk with Explainable AI In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pp

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-03T15:01:41.756239Z

Source-reported events for the cited work

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Observation 5a8e9336-9dbd-463f-8e29-e06dc040e6ba · outbound

This paper cites https://jacobgil.github.io/deeplearning/ vision-transformer-explainability.

Modeling Day-Long ECG Signals to Predict Heart Failure Risk with Explainable AI https://jacobgil.github.io/deeplearning/ vision-transformer-explainability

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-03T15:01:41.848435Z

Source-reported events for the cited work

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Observation bfc25217-edf8-4e88-b1d7-e77dfe281de7 · outbound

This paper cites Circulation145(2), 122–133 (2022) https://doi.org/10.1161/CIRCULATIONAHA.121.057480.

Modeling Day-Long ECG Signals to Predict Heart Failure Risk with Explainable AI Circulation145(2), 122–133 (2022) https://doi.org/10.1161/CIRCULATIONAHA.121.057480

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-03T15:01:41.952946Z

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Observation 9551b239-6d01-4c4c-932f-b73b121e0550 · outbound

This paper cites European Heart Journal42(38), 3948–3961 (2021) https://doi.org/10.1093/EURHEARTJ/EHAB588.

Modeling Day-Long ECG Signals to Predict Heart Failure Risk with Explainable AI European Heart Journal42(38), 3948–3961 (2021) https://doi.org/10.1093/EURHEARTJ/EHAB588

Reference 21

Resolution: verified exact; doi, observed 2026-08-03T15:04:06.543260Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 20b2d526-243e-4dd2-88f1-1bdee5e331b9 · outbound

This paper cites npj Digital Medicine6, 169–169 (2023) https://doi.org/10.1038/s41746-023-00916-6.

Modeling Day-Long ECG Signals to Predict Heart Failure Risk with Explainable AI npj Digital Medicine6, 169–169 (2023) https://doi.org/10.1038/s41746-023-00916-6

Reference 22

Resolution: verified exact; doi, observed 2026-08-03T15:04:06.333097Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation a699562f-7315-46a1-8f74-7dbd5956c4e6 · outbound

This paper cites The American Journal of Cardiology168, 105–109 (2022) https://doi.org/10.1016/j.amjcard.2021.12.017.

Modeling Day-Long ECG Signals to Predict Heart Failure Risk with Explainable AI The American Journal of Cardiology168, 105–109 (2022) https://doi.org/10.1016/j.amjcard.2021.12.017

Reference 23

Resolution: verified exact; doi, observed 2026-08-03T15:04:06.122726Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation b1d24ee4-cb4b-4405-acfd-c8cb10753af2 · outbound

This paper cites Circulation: Heart 15 Failure14(2), 007761 (2021) https://doi.org/10.1161/CIRCHEARTF AILURE.120.007761.

Modeling Day-Long ECG Signals to Predict Heart Failure Risk with Explainable AI Circulation: Heart 15 Failure14(2), 007761 (2021) https://doi.org/10.1161/CIRCHEARTF AILURE.120.007761

Reference 24

Resolution: malformed identifier; doi_truncated, observed 2026-08-03T15:04:05.957097Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 2639689c-f244-4b7e-9d9f-326a8547799c · outbound

This paper cites European Heart Journal46(11), 1044–1053 (2025) https://doi.org/10.1093/eurheartj/ehae914.

Modeling Day-Long ECG Signals to Predict Heart Failure Risk with Explainable AI European Heart Journal46(11), 1044–1053 (2025) https://doi.org/10.1093/eurheartj/ehae914

Reference 25

Resolution: verified exact; doi, observed 2026-08-03T15:04:05.744026Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation a2b1396b-ff82-4507-a187-1da7ddaf55cf · outbound

This paper cites Cardiovascular Digital Health Journal4(6), 183–190 (2023) https://doi.org/10.1016/j.cvdhj.2023.11.003.

Modeling Day-Long ECG Signals to Predict Heart Failure Risk with Explainable AI Cardiovascular Digital Health Journal4(6), 183–190 (2023) https://doi.org/10.1016/j.cvdhj.2023.11.003

Reference 26

Resolution: verified exact; doi, observed 2026-08-03T15:04:05.562567Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation cee210b8-7bfd-4648-8882-82b2f22210f1 · outbound

This paper cites European Heart Journal - Digital Health2(4), 626–634 (2021) https://doi.org/10.1093/ehjdh/ztab080.

Modeling Day-Long ECG Signals to Predict Heart Failure Risk with Explainable AI European Heart Journal - Digital Health2(4), 626–634 (2021) https://doi.org/10.1093/ehjdh/ztab080

Reference 27

Resolution: verified exact; doi, observed 2026-08-03T15:04:05.357803Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 13c069b3-1c06-4202-b08f-af5af5749297 · outbound

This paper cites IEEE Transactions on Neural Systems and Rehabilitation Engineering27(3), 400–410 (2019) https://doi.org/10.1109/TNSRE.2019.2896659.

Modeling Day-Long ECG Signals to Predict Heart Failure Risk with Explainable AI IEEE Transactions on Neural Systems and Rehabilitation Engineering27(3), 400–410 (2019) https://doi.org/10.1109/TNSRE.2019.2896659

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-03T15:01:42.685393Z

Source-reported events for the cited work

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Observation 5a55279c-4889-4a27-9ccb-7f7b39ad6cc0 · outbound

This paper cites Nature Medicine30(5), 1461–1470 (2024) https://doi.org/10.1038/s41591-024-02961-4.

Modeling Day-Long ECG Signals to Predict Heart Failure Risk with Explainable AI Nature Medicine30(5), 1461–1470 (2024) https://doi.org/10.1038/s41591-024-02961-4

Reference 29

Resolution: verified exact; doi, observed 2026-08-03T15:04:05.178012Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 9fefed90-ddb0-4e16-97bc-ac0e56a5b904 · outbound

This paper cites Attention is not Explanation.

Modeling Day-Long ECG Signals to Predict Heart Failure Risk with Explainable AI Attention is not Explanation

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-03T15:01:42.820352Z

Source-reported events for the cited work

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Observation b5560222-b9c4-488c-baa4-a4d38669f0e4 · outbound

This paper cites 782–791 (2021).

Modeling Day-Long ECG Signals to Predict Heart Failure Risk with Explainable AI 782–791 (2021)

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-03T15:01:42.900465Z

Source-reported events for the cited work

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Observation 0ccdecad-ee21-4f0e-88e3-5bebbbb1fb50 · outbound

This paper cites GMAR: Gradient-Driven Multi-Head Attention Rollout for Vision Transformer Interpretability.

Modeling Day-Long ECG Signals to Predict Heart Failure Risk with Explainable AI GMAR: Gradient-Driven Multi-Head Attention Rollout for Vision Transformer Interpretability

Reference 32

Resolution: verified exact; local_arxiv, observed 2026-08-03T15:04:04.976042Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation c7c8e3f6-271e-434e-8663-f53545588d90 · outbound

This paper cites Advanced Drug Delivery Reviews59(9-10), 940–951 (2007) https://doi.org/10.1016/J.ADDR.2006.10.011.

Modeling Day-Long ECG Signals to Predict Heart Failure Risk with Explainable AI Advanced Drug Delivery Reviews59(9-10), 940–951 (2007) https://doi.org/10.1016/J.ADDR.2006.10.011

Reference 33

Resolution: verified exact; doi, observed 2026-08-03T15:04:04.766752Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 00d56cb6-f175-4def-938f-8f4a55c75c40 · outbound

This paper cites Journal of the American College of Cardiology66(2), 101–109 (2015) https://doi.org/10.1016/J.JACC.2015.04.062.

Modeling Day-Long ECG Signals to Predict Heart Failure Risk with Explainable AI Journal of the American College of Cardiology66(2), 101–109 (2015) https://doi.org/10.1016/J.JACC.2015.04.062

Reference 34

Resolution: verified exact; doi, observed 2026-08-03T15:04:04.550477Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation a015758b-ddde-4f43-ba30-c9b4b0d8326f · outbound

This paper cites The American Journal of Cardiology91(6), 2–8 (2003) https://doi.org/10.1016/S0002-9149(02)03373-8.

Modeling Day-Long ECG Signals to Predict Heart Failure Risk with Explainable AI The American Journal of Cardiology91(6), 2–8 (2003) https://doi.org/10.1016/S0002-9149(02)03373-8

Reference 35

Resolution: verified exact; doi, observed 2026-08-03T15:04:04.347991Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 43117859-17c0-4e00-a329-63ee7a092fad · outbound

This paper cites Journal of Clinical Medicine11(9), 2510–2510 (2022) https://doi.org/10.3390/JCM11092510.

Modeling Day-Long ECG Signals to Predict Heart Failure Risk with Explainable AI Journal of Clinical Medicine11(9), 2510–2510 (2022) https://doi.org/10.3390/JCM11092510

Reference 36

Resolution: verified exact; doi, observed 2026-08-03T15:04:04.194122Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation fabfbfc3-cfa8-496c-9eee-e296cf4b4d35 · outbound

This paper cites JAMA310(1), 66–74 (2013) https://doi.org/10.1001/jama.2013.7588.

Modeling Day-Long ECG Signals to Predict Heart Failure Risk with Explainable AI JAMA310(1), 66–74 (2013) https://doi.org/10.1001/jama.2013.7588

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-03T15:01:43.647720Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b2733dad-4a8b-4703-9dc1-f065c1132ad2 · outbound

This paper cites JAMA310(1), 44–45 (2013) https://doi.org/10.1001/jama.2013.7589.

Modeling Day-Long ECG Signals to Predict Heart Failure Risk with Explainable AI JAMA310(1), 44–45 (2013) https://doi.org/10.1001/jama.2013.7589

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-03T15:01:43.795201Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9feb826e-b487-4980-be5e-17b74abe495f · outbound

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

Modeling Day-Long ECG Signals to Predict Heart Failure Risk with Explainable AI ECG-FM: An Open Electrocardiogram Foundation Model

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-03T15:01:43.849024Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 30456234-0314-479e-aae2-012ecaa18537 · outbound

This paper cites Interpretable Pre-Trained Transformers for Heart Time-Series Data.

Modeling Day-Long ECG Signals to Predict Heart Failure Risk with Explainable AI Interpretable Pre-Trained Transformers for Heart Time-Series Data

Reference 40

Resolution: verified exact; local_arxiv, observed 2026-08-03T15:04:04.013381Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 32aa029a-47ed-4adb-99e3-5790a3f65d4b · outbound

This paper cites An Electrocardiogram Foundation Model Built on over 10 Million Recordings with External Evaluation across Multiple Domains.

Modeling Day-Long ECG Signals to Predict Heart Failure Risk with Explainable AI An Electrocardiogram Foundation Model Built on over 10 Million Recordings with External Evaluation across Multiple Domains

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-03T15:01:44.119989Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f2570c15-96bc-4872-b339-55de6570ab58 · outbound

This paper cites SiamAF: Learning Shared Information from ECG and PPG Signals for Robust Atrial Fibrillation Detection.

Modeling Day-Long ECG Signals to Predict Heart Failure Risk with Explainable AI SiamAF: Learning Shared Information from ECG and PPG Signals for Robust Atrial Fibrillation Detection

Reference 42

Resolution: verified exact; local_arxiv, observed 2026-08-03T15:04:03.830029Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation bda0dbfd-69d5-4043-97ea-76d3f13e0f15 · outbound

This paper cites In: The Twelfth International Conference on Learning Representations - ICLR 2024 (2024).https://openreview.net/forum?id=pC3WJHf51j.

Modeling Day-Long ECG Signals to Predict Heart Failure Risk with Explainable AI In: The Twelfth International Conference on Learning Representations - ICLR 2024 (2024).https://openreview.net/forum?id=pC3WJHf51j

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-03T15:01:44.424384Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5ba8c809-d19e-428a-b23d-f8b4c6a2ce0d · outbound

This paper cites Transactions on Machine Learning Research (2023).

Modeling Day-Long ECG Signals to Predict Heart Failure Risk with Explainable AI Transactions on Machine Learning Research (2023)

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-03T15:01:44.545335Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ca213582-d28e-4f8e-af75-2e37af7acc52 · outbound

This paper cites In: Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining.

Modeling Day-Long ECG Signals to Predict Heart Failure Risk with Explainable AI In: Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-03T15:01:44.667072Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fca1041a-d24a-4bad-baf3-b06ea766e794 · outbound

This paper cites Technical report, Jerusalem (2023).

Modeling Day-Long ECG Signals to Predict Heart Failure Risk with Explainable AI Technical report, Jerusalem (2023)

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-03T15:01:44.847871Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 166a522c-8c1e-42b5-8a07-0c7b6daa12d8 · outbound

This paper cites Behavior Research Methods53(4), 1689–1696 (2021) https://doi.org/10.3758/S13428-020-01516-Y/TABLES/3.

Modeling Day-Long ECG Signals to Predict Heart Failure Risk with Explainable AI Behavior Research Methods53(4), 1689–1696 (2021) https://doi.org/10.3758/S13428-020-01516-Y/TABLES/3

Reference 47

Resolution: verified exact; doi, observed 2026-08-03T15:04:03.557571Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 4b619963-5805-4a1e-9d33-9f7f9ae7ea49 · outbound

This paper cites In: 2021 Computing in Cardiology (CinC), vol.

Modeling Day-Long ECG Signals to Predict Heart Failure Risk with Explainable AI In: 2021 Computing in Cardiology (CinC), vol

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-03T15:01:45.147111Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b5a254ba-786d-4509-9dc5-0a5a50e79ada · outbound

This paper cites Sobel, J., Alexandrovich, A., Charlton, P., Marton Aron Goda, D.: PhysioZoo: The Open Physiological Biomarkers Resource.

Modeling Day-Long ECG Signals to Predict Heart Failure Risk with Explainable AI Sobel, J., Alexandrovich, A., Charlton, P., Marton Aron Goda, D.: PhysioZoo: The Open Physiological Biomarkers Resource

Reference 49

Resolution: verified exact; doi, observed 2026-08-03T15:04:03.387395Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 3436ca5d-8b08-44be-9ddd-88c7fcc13de7 · outbound

This paper cites Journal of Machine Learning Research12(85), 2825–2830 (2011).

Modeling Day-Long ECG Signals to Predict Heart Failure Risk with Explainable AI Journal of Machine Learning Research12(85), 2825–2830 (2011)

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-03T15:01:45.493782Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b5f99f99-6d78-477e-90e5-14ca13a42475 · outbound

This paper cites Journal of Open Source Software4(40), 1317 (2019) https://doi.org/10.21105/joss.01317.

Modeling Day-Long ECG Signals to Predict Heart Failure Risk with Explainable AI Journal of Open Source Software4(40), 1317 (2019) https://doi.org/10.21105/joss.01317

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-03T15:01:45.614615Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 76a1c4c7-8671-43a7-b09b-a1b2faa6ab44 · outbound

This paper cites BMC Medical Research Methodology20(1), 53 (2020) https://doi.org/10.1186/s12874-019-0890-x.

Modeling Day-Long ECG Signals to Predict Heart Failure Risk with Explainable AI BMC Medical Research Methodology20(1), 53 (2020) https://doi.org/10.1186/s12874-019-0890-x

Reference 52

Resolution: verified exact; doi, observed 2026-08-03T15:04:03.180026Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 543f5ee2-dab0-4601-980f-4bc0696a40ee · outbound

This paper cites recording date before 2010 or after 2023.

Modeling Day-Long ECG Signals to Predict Heart Failure Risk with Explainable AI recording date before 2010 or after 2023

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-03T15:01:45.905681Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Coverage vector

Reference resolution

Outbound references

Pith citing papers