Paper Citation Record · LEDGER

Early Risk Prediction of Pediatric Cardiac Arrest from Electronic Health Records via Multimodal Fused Transformer

As of 21 August 2026, this Paper Citation Record lists 38 of 38 outbound references and 0 inbound Pith citation observations for arXiv:2502.07158.

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

pith.paper-citation-record.v1
2502.07158 v3

Coverage vector

measured 38 of 38 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-08T13:41:00.502459Z

measured 38 of 38 standing notices

One-hop event checks from named stored sources.

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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

38 of 38 outbound references displayed

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External citation measurements

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Outbound references

Observation f9541350-094c-45ea-88ec-69c217cd1e79 · outbound

This paper cites Risk factors and outcomes for recurrent paediatric in-hospital cardiac arrest: Retrospective multicenter cohort study,.

Early Risk Prediction of Pediatric Cardiac Arrest from Electronic Health Records via Multimodal Fused Transformer Risk factors and outcomes for recurrent paediatric in-hospital cardiac arrest: Retrospective multicenter cohort study,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T13:41:01.073812Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 6b1fb136-bedf-44be-8ff8-57154acf6a2f · outbound

This paper cites Pic, a paediatric-specific intensive care database,.

Early Risk Prediction of Pediatric Cardiac Arrest from Electronic Health Records via Multimodal Fused Transformer Pic, a paediatric-specific intensive care database,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T13:41:01.059315Z

Source-reported events for the cited work

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Observation df01f8bc-9e5c-49bd-a797-f7ba7dfd5b84 · outbound

This paper cites Pediatric in-hospital cardiac arrest and cardiopulmonary resuscitation in the united states: a review,.

Early Risk Prediction of Pediatric Cardiac Arrest from Electronic Health Records via Multimodal Fused Transformer Pediatric in-hospital cardiac arrest and cardiopulmonary resuscitation in the united states: a review,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T13:41:01.044638Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 83c08992-1621-471c-bc93-524d10af9c89 · outbound

This paper cites an unresolved cited work.

Early Risk Prediction of Pediatric Cardiac Arrest from Electronic Health Records via Multimodal Fused Transformer Unresolved cited work

Reference 4

Resolution: unresolved; raw_fallback, observed 2026-08-08T13:41:01.029209Z

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Observation a0cc3595-d12e-4814-8068-02cbf293cc4f · outbound

This paper cites Prognostic accuracy of machine learning models for in-hospital mortality among children with phoenix sepsis admitted to the pediatric intensive care unit,.

Early Risk Prediction of Pediatric Cardiac Arrest from Electronic Health Records via Multimodal Fused Transformer Prognostic accuracy of machine learning models for in-hospital mortality among children with phoenix sepsis admitted to the pediatric intensive care unit,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T13:41:01.013285Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 9a75eaf2-1cf6-4472-b6e6-2af925ec930f · outbound

This paper cites Using machine learning to predict cardiac arrest in the pediatric cardiac intensive care unit,.

Early Risk Prediction of Pediatric Cardiac Arrest from Electronic Health Records via Multimodal Fused Transformer Using machine learning to predict cardiac arrest in the pediatric cardiac intensive care unit,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T13:41:00.997670Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 1f1e3453-1ccb-43ea-9763-d0c86929b4e2 · outbound

This paper cites Ehrshot: An ehr benchmark for few-shot evaluation of foundation models,.

Early Risk Prediction of Pediatric Cardiac Arrest from Electronic Health Records via Multimodal Fused Transformer Ehrshot: An ehr benchmark for few-shot evaluation of foundation models,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T13:41:00.980315Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation b7f77b78-3728-453c-98cc-c2878956d7e5 · outbound

This paper cites Detecting and managing deterioration in children,.

Early Risk Prediction of Pediatric Cardiac Arrest from Electronic Health Records via Multimodal Fused Transformer Detecting and managing deterioration in children,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T13:41:00.962634Z

Source-reported events for the cited work

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Observation c063e276-0b7a-419f-b3d5-a7af62e4f8fd · outbound

This paper cites The inadequate oxygen delivery index and its correlation with venous saturation in the pediatric cardiac intensive care unit,.

Early Risk Prediction of Pediatric Cardiac Arrest from Electronic Health Records via Multimodal Fused Transformer The inadequate oxygen delivery index and its correlation with venous saturation in the pediatric cardiac intensive care unit,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T13:41:00.948109Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 8550c840-1619-4280-9a9b-ef015f1aea2e · outbound

This paper cites Xgboost: A scalable tree boosting system,.

Early Risk Prediction of Pediatric Cardiac Arrest from Electronic Health Records via Multimodal Fused Transformer Xgboost: A scalable tree boosting system,

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-08T13:41:00.273062Z

Source-reported events for the cited work

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Observation d42ce20d-f339-4eef-b99e-293b2204eef2 · outbound

This paper cites Scalable and accurate deep learning with electronic health records,.

Early Risk Prediction of Pediatric Cardiac Arrest from Electronic Health Records via Multimodal Fused Transformer Scalable and accurate deep learning with electronic health records,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T13:41:00.922687Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 057da507-5440-433c-a435-7733a6d55e9e · outbound

This paper cites MOMENT: A Family of Open Time-series Foundation Models.

Early Risk Prediction of Pediatric Cardiac Arrest from Electronic Health Records via Multimodal Fused Transformer MOMENT: A Family of Open Time-series Foundation Models

Reference 12

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Source-reported events for the cited work

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Observation 7a894712-0b5a-479a-af34-6af54b1469e3 · outbound

This paper cites Lag-llama: Towards foundation models for time series forecasting,.

Early Risk Prediction of Pediatric Cardiac Arrest from Electronic Health Records via Multimodal Fused Transformer Lag-llama: Towards foundation models for time series forecasting,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T13:41:00.907186Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 8685e206-218b-4f03-a639-d845429004f8 · outbound

This paper cites Tiny time mixers (ttms): Fast pre-trained models for enhanced zero/few-shot forecasting of multivariate time series.

Early Risk Prediction of Pediatric Cardiac Arrest from Electronic Health Records via Multimodal Fused Transformer Tiny time mixers (ttms): Fast pre-trained models for enhanced zero/few-shot forecasting of multivariate time series

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T13:41:00.890056Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 5e4cc357-7f5f-4ea3-a29e-2b5587a90810 · outbound

This paper cites Multimodal automl on structured tables with text fields,.

Early Risk Prediction of Pediatric Cardiac Arrest from Electronic Health Records via Multimodal Fused Transformer Multimodal automl on structured tables with text fields,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T13:41:00.875806Z

Source-reported events for the cited work

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Observation c3c45afb-7ad5-4c51-8773-a8e447ef13a2 · outbound

This paper cites MuG: A multimodal classification benchmark on game data with tabular, textual, and visual fields,.

Early Risk Prediction of Pediatric Cardiac Arrest from Electronic Health Records via Multimodal Fused Transformer MuG: A multimodal classification benchmark on game data with tabular, textual, and visual fields,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T13:41:00.861474Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation d22d84de-0b33-4aa2-b514-1b7ff86de45a · outbound

This paper cites TabTransformer: Tabular Data Modeling Using Contextual Embeddings.

Early Risk Prediction of Pediatric Cardiac Arrest from Electronic Health Records via Multimodal Fused Transformer TabTransformer: Tabular Data Modeling Using Contextual Embeddings

Reference 17

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Observation edb7e1b7-15eb-492a-bd08-d40db0ba3c09 · outbound

This paper cites Revisiting deep learning models for tabular data,.

Early Risk Prediction of Pediatric Cardiac Arrest from Electronic Health Records via Multimodal Fused Transformer Revisiting deep learning models for tabular data,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T13:41:00.846749Z

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Observation 9345023a-2c8c-426f-81aa-680e8143645c · outbound

This paper cites A large language model for electronic health records,.

Early Risk Prediction of Pediatric Cardiac Arrest from Electronic Health Records via Multimodal Fused Transformer A large language model for electronic health records,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T13:41:00.832198Z

Source-reported events for the cited work

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Observation 1c5c0690-a7ed-4f00-b9d9-285b9a5960c1 · outbound

This paper cites DeLLiriuM: A large language model for delirium prediction in the ICU using structured EHR.

Early Risk Prediction of Pediatric Cardiac Arrest from Electronic Health Records via Multimodal Fused Transformer DeLLiriuM: A large language model for delirium prediction in the ICU using structured EHR

Reference 20

Resolution: verified exact; local_arxiv, observed 2026-08-08T13:41:00.574121Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation a5db53bb-f9e9-44cb-beb6-050ce49a5dde · outbound

This paper cites Attention is all you need,.

Early Risk Prediction of Pediatric Cardiac Arrest from Electronic Health Records via Multimodal Fused Transformer Attention is all you need,

Reference 21

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Source-reported events for the cited work

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Observation 13b51a15-f12f-48ac-9fe5-67ebff318291 · outbound

This paper cites Uncertainty-aware pre-trained foundation models for patient risk prediction via gaussian process,.

Early Risk Prediction of Pediatric Cardiac Arrest from Electronic Health Records via Multimodal Fused Transformer Uncertainty-aware pre-trained foundation models for patient risk prediction via gaussian process,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T13:41:00.809278Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 03ca608a-45e5-4232-96bc-5cfb2294525e · outbound

This paper cites Adapting a generative pretrained transformer achieves sota performance in assess- ing diverse physiological functions using only photoplethysmography signals: A gpt-ppg approach,.

Early Risk Prediction of Pediatric Cardiac Arrest from Electronic Health Records via Multimodal Fused Transformer Adapting a generative pretrained transformer achieves sota performance in assess- ing diverse physiological functions using only photoplethysmography signals: A gpt-ppg approach,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T13:41:00.795313Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation dfcb41de-366f-48a3-a515-49b9c65f050c · outbound

This paper cites Ehragent: Code empowers large language models for few-shot complex tabular reasoning on electronic health records,.

Early Risk Prediction of Pediatric Cardiac Arrest from Electronic Health Records via Multimodal Fused Transformer Ehragent: Code empowers large language models for few-shot complex tabular reasoning on electronic health records,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T13:41:00.780983Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation a24be43d-4d5b-4d1e-8c52-39aa169adc78 · outbound

This paper cites Bert: Pre-training of deep bidirectional transformers for language understanding,.

Early Risk Prediction of Pediatric Cardiac Arrest from Electronic Health Records via Multimodal Fused Transformer Bert: Pre-training of deep bidirectional transformers for language understanding,

Reference 25

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Source-reported events for the cited work

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Observation 66da64e4-df30-4ed0-870c-d0813f0e5df6 · outbound

This paper cites Clinical laboratory reference intervals in pediatrics: the caliper initiative,.

Early Risk Prediction of Pediatric Cardiac Arrest from Electronic Health Records via Multimodal Fused Transformer Clinical laboratory reference intervals in pediatrics: the caliper initiative,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T13:41:00.757222Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 69c4bc46-8179-418b-a0e1-eede1bc3d794 · outbound

This paper cites Focal loss for dense object detection,.

Early Risk Prediction of Pediatric Cardiac Arrest from Electronic Health Records via Multimodal Fused Transformer Focal loss for dense object detection,

Reference 27

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Source-reported events for the cited work

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Observation dd7b1163-84e0-482a-985a-4fd03c7f2ddf · outbound

This paper cites Use of deep learning to develop continuous-risk models for adverse event prediction from electronic health records,.

Early Risk Prediction of Pediatric Cardiac Arrest from Electronic Health Records via Multimodal Fused Transformer Use of deep learning to develop continuous-risk models for adverse event prediction from electronic health records,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T13:41:00.733162Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 44092ce7-07a7-4c86-b483-c05661850cd1 · outbound

This paper cites Dynamic programming algorithm optimiza- tion for spoken word recognition,.

Early Risk Prediction of Pediatric Cardiac Arrest from Electronic Health Records via Multimodal Fused Transformer Dynamic programming algorithm optimiza- tion for spoken word recognition,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T13:41:00.717895Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation a1307dba-fe05-4774-8476-eae51fc772ab · outbound

This paper cites Fast global alignment kernels,.

Early Risk Prediction of Pediatric Cardiac Arrest from Electronic Health Records via Multimodal Fused Transformer Fast global alignment kernels,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T13:41:00.701658Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 27d6b673-b81b-4e30-9678-2d320ec2d5d1 · outbound

This paper cites Tslearn, a machine learning toolkit for time series data,.

Early Risk Prediction of Pediatric Cardiac Arrest from Electronic Health Records via Multimodal Fused Transformer Tslearn, a machine learning toolkit for time series data,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T13:41:00.686977Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 75de9243-fdd0-4018-a641-2c3329b7e9ec · outbound

This paper cites Lightgbm: A highly efficient gradient boosting decision tree,.

Early Risk Prediction of Pediatric Cardiac Arrest from Electronic Health Records via Multimodal Fused Transformer Lightgbm: A highly efficient gradient boosting decision tree,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T13:41:00.672279Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 63f5af35-104b-4a01-a73b-f6636d8d21c2 · outbound

This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.

Early Risk Prediction of Pediatric Cardiac Arrest from Electronic Health Records via Multimodal Fused Transformer BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 33

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This paper cites AutoGluon-Tabular: Robust and Accurate AutoML for Structured Data.

Early Risk Prediction of Pediatric Cardiac Arrest from Electronic Health Records via Multimodal Fused Transformer AutoGluon-Tabular: Robust and Accurate AutoML for Structured Data

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-08T13:41:00.380062Z

Source-reported events for the cited work

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Observation 431e90a4-8189-44cb-9633-87b32c770e0b · outbound

This paper cites Time series classification from scratch with deep neural networks: A strong baseline,.

Early Risk Prediction of Pediatric Cardiac Arrest from Electronic Health Records via Multimodal Fused Transformer Time series classification from scratch with deep neural networks: A strong baseline,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T13:41:00.657680Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 9a11f188-e54b-4540-8e9b-0052aaa86b7c · outbound

This paper cites Pay attention to mlps,.

Early Risk Prediction of Pediatric Cardiac Arrest from Electronic Health Records via Multimodal Fused Transformer Pay attention to mlps,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T13:41:00.643228Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 29659113-97d8-4bff-8256-7c2c3e4e37bd · outbound

This paper cites tsai - a state-of-the-art deep learning library for time series and sequential data,.

Early Risk Prediction of Pediatric Cardiac Arrest from Electronic Health Records via Multimodal Fused Transformer tsai - a state-of-the-art deep learning library for time series and sequential data,

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-08T13:41:00.497821Z

Source-reported events for the cited work

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Observation 6e8774f8-66d6-4605-98e9-bbb45f1f4210 · outbound

This paper cites Permutation importance: a corrected feature importance measure,.

Early Risk Prediction of Pediatric Cardiac Arrest from Electronic Health Records via Multimodal Fused Transformer Permutation importance: a corrected feature importance measure,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T13:41:00.619499Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Pith citing papers

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