Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-15T22:04:33.112647Z
Paper Citation Record · LEDGER
Congenital Heart Disease recognition using Deep Learning/Transformer models
As of 18 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.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
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
- parse uncertain0
- malformed identifier0
- 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 2026-08-18T06:34:40.430872+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 2026-08-18T06:34:40.430872+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 2026-08-18T06:34:40.430872+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 2026-08-18T06:34:40.430872+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 2026-08-18T06:34:40.430872+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 2026-08-18T06:34:40.430872+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 2026-08-18T06:34:40.430872+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 2026-08-18T06:34:40.430872+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 2026-08-18T06:34:40.430872+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 2026-08-18T06:34:40.430872+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 2026-08-18T06:34:40.430872+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 2026-08-18T06:34:40.430872+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 2026-08-18T06:34:40.430872+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 2026-08-18T06:34:40.430872+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 2026-08-18T06:34:40.430872+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 2026-08-18T06:34:40.430872+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 2026-08-18T06:34:40.430872+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 2026-08-18T06:34:40.430872+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 2026-08-18T06:34:40.430872+00:00.
Pith citing papers
No inbound Pith citation observations are available.