Paper Citation Record · LEDGER

Congenital Heart Disease recognition using Deep Learning/Transformer models

As of 19 August 2026, this Paper Citation Record lists 19 of 19 outbound references and 0 inbound Pith citation observations for arXiv:2505.08242.

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

pith.paper-citation-record.v1
2505.08242 v1

Coverage vector

measured 19 of 19 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T22:04:33.112647Z

measured 19 of 19 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+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

19 of 19 outbound references displayed

verified exact4
verified fuzzy14
unresolved0
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metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f53a1c0f-065d-4588-8393-b04b0e2890f7 · outbound

This paper cites The heart sound dataset consists of 941 participants and 941 audio recordings, each approximately 20 seconds long, totaling over 5 hours in duration.

Congenital Heart Disease recognition using Deep Learning/Transformer models The heart sound dataset consists of 941 participants and 941 audio recordings, each approximately 20 seconds long, totaling over 5 hours in duration

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:04:33.464746Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 2330f7be-a900-49a3-93cc-ecfefac8bbb6 · outbound

This paper cites Originally the storage format of the files was DICOM.

Congenital Heart Disease recognition using Deep Learning/Transformer models Originally the storage format of the files was DICOM

Reference 2

Resolution: verified exact; raw_fallback, observed 2026-08-15T22:04:33.313903Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 453e6cf5-5049-4f1c-a7e1-6ba1809c2145 · outbound

This paper cites Long-term outcomes after myocardial infarction in middle-aged and older patients with congenital heart disease—a nationwide study,.

Congenital Heart Disease recognition using Deep Learning/Transformer models Long-term outcomes after myocardial infarction in middle-aged and older patients with congenital heart disease—a nationwide study,

Reference 3

Resolution: verified exact; doi, observed 2026-08-15T22:04:33.157645Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation eee863ea-2157-4bc4-a38d-a67ad73edaf1 · outbound

This paper cites Diagnostic value of fetal echocardiography for congenital heart disease: A systematic review and meta-analysis,.

Congenital Heart Disease recognition using Deep Learning/Transformer models Diagnostic value of fetal echocardiography for congenital heart disease: A systematic review and meta-analysis,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:04:33.453384Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 582f68b0-1d43-48f4-981c-27ea1817c7aa · outbound

This paper cites The Role of Machine Learning in Congenital Heart Disease Diagnosis: Datasets, Algorithms, and Insights.

Congenital Heart Disease recognition using Deep Learning/Transformer models The Role of Machine Learning in Congenital Heart Disease Diagnosis: Datasets, Algorithms, and Insights

Reference 5

Resolution: verified exact; local_arxiv, observed 2026-08-15T22:04:33.250777Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 88d218df-7a99-475a-acb9-f35060e8f9ee · outbound

This paper cites Detection and diagnosis of congenital heart disease from chest x-rays with deep learning models,.

Congenital Heart Disease recognition using Deep Learning/Transformer models Detection and diagnosis of congenital heart disease from chest x-rays with deep learning models,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:04:33.442684Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation d3460174-de3e-4eb1-b454-63892e9f010e · outbound

This paper cites Zchsound: Open-source zju paediatric heart sound database with congenital heart disease,.

Congenital Heart Disease recognition using Deep Learning/Transformer models Zchsound: Open-source zju paediatric heart sound database with congenital heart disease,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:04:33.433001Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 454be57e-71ed-4f73-8a99-96f4f3097d83 · outbound

This paper cites Assisting Heart Valve Diseases Diagnosis via Transformer-Based Classification of Heart Sound Signals,.

Congenital Heart Disease recognition using Deep Learning/Transformer models Assisting Heart Valve Diseases Diagnosis via Transformer-Based Classification of Heart Sound Signals,

Reference 8

Resolution: verified exact; doi, observed 2026-08-15T22:04:33.145703Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation d5b8db7c-4961-49c9-9622-4c962c8d2074 · outbound

This paper cites Heart sounds classification with a fuzzy neural network method with structure learning,.

Congenital Heart Disease recognition using Deep Learning/Transformer models Heart sounds classification with a fuzzy neural network method with structure learning,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:04:33.423858Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 31c34b60-2151-41a9-9e06-97779961f574 · outbound

This paper cites Heart sound classification based on scaled spectrogram and partial least squares regression,.

Congenital Heart Disease recognition using Deep Learning/Transformer models Heart sound classification based on scaled spectrogram and partial least squares regression,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:04:33.414520Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 546ef40e-a1df-4a98-baa8-74b77936862f · outbound

This paper cites Classification of heart sound signal using curve fitting and fractal dimension,.

Congenital Heart Disease recognition using Deep Learning/Transformer models Classification of heart sound signal using curve fitting and fractal dimension,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:04:33.403514Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 8cd4b0c8-1727-47b5-9bb0-515746744e3a · outbound

This paper cites CHD- CXR: A De-identified Publicly Available Dataset of Chest X- ray for Congenital Heart Disease,.

Congenital Heart Disease recognition using Deep Learning/Transformer models CHD- CXR: A De-identified Publicly Available Dataset of Chest X- ray for Congenital Heart Disease,

Reference 12

Resolution: metadata mismatch; raw_fallback, observed 2026-08-15T22:04:33.235646Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 2d038524-46aa-4920-8ee9-ea7b68967a72 · outbound

This paper cites Jiang, J.

Congenital Heart Disease recognition using Deep Learning/Transformer models Jiang, J

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:04:33.392268Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 49ad6ae7-ce48-47f7-8181-007af6bb86cd · outbound

This paper cites Genetic contribution to congenital heart disease (chd),.

Congenital Heart Disease recognition using Deep Learning/Transformer models Genetic contribution to congenital heart disease (chd),

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:04:33.381500Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 19129712-f50a-41de-bf5c-4c173ef77dfe · outbound

This paper cites Theory of edge detection,.

Congenital Heart Disease recognition using Deep Learning/Transformer models Theory of edge detection,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:04:33.370571Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation c2985067-b14e-42e7-b4f2-9f1b3322a9dc · outbound

This paper cites Gaussian blurring technique for detecting and classifying acute lymphoblastic leukemia cancer cells from microscopic biopsy images,.

Congenital Heart Disease recognition using Deep Learning/Transformer models Gaussian blurring technique for detecting and classifying acute lymphoblastic leukemia cancer cells from microscopic biopsy images,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:04:33.360332Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 48b3f72a-b57a-4af6-b001-11978e52f0b2 · outbound

This paper cites Can ai help in screening viral and covid-19 pneumonia?.

Congenital Heart Disease recognition using Deep Learning/Transformer models Can ai help in screening viral and covid-19 pneumonia?

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:04:33.349227Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation f0e90baa-0465-40f0-a3ba-e4270fe7bf56 · outbound

This paper cites Automated abnormality classification of chest radiographs using deep convolutional neural networks,.

Congenital Heart Disease recognition using Deep Learning/Transformer models Automated abnormality classification of chest radiographs using deep convolutional neural networks,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:04:33.338306Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 279278e1-d0e2-499c-a523-5c96bf3a0897 · outbound

This paper cites Efficient deep network architectures for fast chest x-ray tuberculosis screening and visualization,.

Congenital Heart Disease recognition using Deep Learning/Transformer models Efficient deep network architectures for fast chest x-ray tuberculosis screening and visualization,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:04:33.326893Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Pith citing papers

No inbound Pith citation observations are available.