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Paper Citation Record · LEDGER

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

As of 9 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.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+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

38 of 38 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

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
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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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

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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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
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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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
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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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
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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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 2026-08-08T06:32:00.761636+00:00.

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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 2026-08-08T06:32:00.761636+00:00.

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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

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-08T13:41:00.264180Z digest=sha256:2a2da03cf1412a9c994efe1b0e4d325db1f296c2cee219c33d31c1d0e66b3530

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 2026-08-08T06:32:00.761636+00:00.

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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

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unresolved
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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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
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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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

Resolution
unresolved
no resolver link, observed 2026-08-08T13:41:00.281583Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T13:41:00.281583Z digest=sha256:4dbca344a2672749e1b9787c71dacdb4c58f72ec3e4a1056a727b32f420ed643

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-08T13:41:00.287052Z digest=sha256:7ec22337064b6068b384dfda3f89834ba1b522e26f230472c92d140ca289b3a5

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 2026-08-08T06:32:00.761636+00:00.

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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

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-08T13:41:00.295732Z digest=sha256:390e291c3fd88f7c89fafd8cf58e97e820d2e59c8a1a9b0fd5249accf1fb5a53

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
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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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

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T13:41:00.304253Z digest=sha256:e1017d50f508e911e886657913d70ba9233151ded9c3a4256089293fd4aa70cd

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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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

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-08T13:41:00.313434Z digest=sha256:aefa5d4ed2fd95a12ac6cfa76aa3b9d75a46b004c09948da2630132d903a337a

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-08T13:41:00.317641Z digest=sha256:16ce5d9492032dc951456ee8df11e1d75058e4676e91288f612550f6e90816c8

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

Resolution
unresolved
no resolver link, observed 2026-08-08T13:41:00.322825Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-08T13:41:00.327013Z digest=sha256:b8a34e6887d25bd7a593496e1f904ee6f5d1058421ced154a3990d08fca2176b

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-08T13:41:00.331506Z digest=sha256:0fbc4b06f14a1bdb6a940bb0d367a53749fea343196065ca3e0eb47501f2b7bf

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-08T13:41:00.335900Z digest=sha256:8dcc6e654e42080be3cf101cc87d6ee04c0932e1f4ce0cf43237c1fda7ac7146

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

Resolution
unresolved
no resolver link, observed 2026-08-08T13:41:00.340396Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T13:41:00.340396Z digest=sha256:d7975c86728a4363241c583dc08945cedc0d54d857a401ca0104c773d4709441

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-08T13:41:00.344734Z digest=sha256:63314db22e7be1e3543b6392a7fa216863bcf06ef51fdd8f4272facab54d763c

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

Resolution
unresolved
no resolver link, observed 2026-08-08T13:41:00.349045Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T13:41:00.349045Z digest=sha256:1b2e51c900f5fb5b5c91dab356acaf1dadcc886b9d683a40f45344623eb4cfc0

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-08T13:41:00.353394Z digest=sha256:74bee56d7d598d7bc673d717a05bf4209f076a51d53df2eeb5e798f25cc2aa5b

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-08T13:41:00.358048Z digest=sha256:e23fa9102c24df04006e3314cc10c4dee77b46908d97b04af4de32abd95bb701

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-08T13:41:00.362265Z digest=sha256:8b84715a8f275fe0e251233f4e782204c8a0f4b8720a199e0c4a4db7cc0d6341

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-08T13:41:00.366444Z digest=sha256:ff870ee36cf9aa0395547e31bbf3406416db720e0d8fcab223bc364642bfd9a6

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-08T13:41:00.370953Z digest=sha256:21f1c8ebf8b971bc9e6cf81586c43341e4fcd7db743bf9a5ae444d5c96860812

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

Resolution
unresolved
no resolver link, observed 2026-08-08T13:41:00.375253Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 806d7d9f-b26d-41e2-84f4-4d11fd4ad494 · outbound

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

Unavailable: canonical work link unavailable.

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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 2026-08-08T06:32:00.761636+00:00.

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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 2026-08-08T06:32:00.761636+00:00.

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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

Unavailable: canonical work link unavailable.

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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 2026-08-08T06:32:00.761636+00:00.

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Pith citing papers

No inbound Pith citation observations are available.