Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-01T10:26:09.783925Z
Paper Citation Record · LEDGER
As of 7 August 2026, this Paper Citation Record lists 13 of 13 outbound references and 0 inbound Pith citation observations for arXiv:2607.27286.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-01T10:26:09.783925Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+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
13 of 13 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 21155378-e9af-4db5-9a13-8fa4d3830be4 · outbound
Toward Multi-Modal Deep Learning for Pulmonary Disease Classification: A Texture-Based Machine Learning Pilot Study on Public Chest X-Ray Data Deep learning applications in chest imaging,
Reference 1
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c1d6cd04-7ba0-4381-af3c-3de862a035c3 · outbound
Toward Multi-Modal Deep Learning for Pulmonary Disease Classification: A Texture-Based Machine Learning Pilot Study on Public Chest X-Ray Data ChestX-ray8: Hospital-scale chest X-ray database and benchmarks on weakly-supervised classification and localization of common thorax diseases,
Reference 2
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 324c3cc3-ae25-43cd-a49c-994493c37ea4 · outbound
Toward Multi-Modal Deep Learning for Pulmonary Disease Classification: A Texture-Based Machine Learning Pilot Study on Public Chest X-Ray Data End-to-end lung cancer screening with three-dimensional deep learning on low-dose chest computed tomography,
Reference 3
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c8574698-43b6-40ef-932a-0c79673c66d7 · outbound
Toward Multi-Modal Deep Learning for Pulmonary Disease Classification: A Texture-Based Machine Learning Pilot Study on Public Chest X-Ray Data Deep learning-enabled medical computer vision,
Reference 4
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1b524024-0c81-43d3-a60f-3189175e1966 · outbound
Toward Multi-Modal Deep Learning for Pulmonary Disease Classification: A Texture-Based Machine Learning Pilot Study on Public Chest X-Ray Data TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation
Reference 5
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4e33ba0d-74a2-4798-a245-26aff5f269f8 · outbound
Toward Multi-Modal Deep Learning for Pulmonary Disease Classification: A Texture-Based Machine Learning Pilot Study on Public Chest X-Ray Data Rethinking medical image classification: Computer vision foundation models and domain-specific fine-tuning,
Reference 6
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d7f41d89-1b8f-463a-9076-ab733388fa2e · outbound
Toward Multi-Modal Deep Learning for Pulmonary Disease Classification: A Texture-Based Machine Learning Pilot Study on Public Chest X-Ray Data Contrastive Learning of Medical Visual Representations from Paired Images and Text
Reference 7
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 43647201-4ccf-40f9-acff-3fea608917c3 · outbound
Toward Multi-Modal Deep Learning for Pulmonary Disease Classification: A Texture-Based Machine Learning Pilot Study on Public Chest X-Ray Data PENet—a scalable deep-learning model for automated diagnosis of pulmonary embolism using volumetric CT imaging,
Reference 8
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b62b25d7-a39f-4be5-ae67-912e7f796fa7 · outbound
Toward Multi-Modal Deep Learning for Pulmonary Disease Classification: A Texture-Based Machine Learning Pilot Study on Public Chest X-Ray Data Swin transformer: Hierarchical vision transformer using shifted windows,
Reference 9
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ceeaea99-b844-4ecf-8b5b-b6e488c9380e · outbound
Toward Multi-Modal Deep Learning for Pulmonary Disease Classification: A Texture-Based Machine Learning Pilot Study on Public Chest X-Ray Data EfficientNetV2: Smaller models and faster training,
Reference 10
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation fb11d780-c5ec-4544-9216-949c4d3fee8a · outbound
Toward Multi-Modal Deep Learning for Pulmonary Disease Classification: A Texture-Based Machine Learning Pilot Study on Public Chest X-Ray Data COVID-19 Image Data Collection
Reference 11
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1920f574-1a31-4b32-b3f5-5085264b0ae7 · outbound
Toward Multi-Modal Deep Learning for Pulmonary Disease Classification: A Texture-Based Machine Learning Pilot Study on Public Chest X-Ray Data Textural features for image classification,
Reference 12
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 73b0789b-d0be-4240-ab1a-5d5f07fa3834 · outbound
Toward Multi-Modal Deep Learning for Pulmonary Disease Classification: A Texture-Based Machine Learning Pilot Study on Public Chest X-Ray Data Histograms of oriented gradients for human detection,
Reference 13
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
No inbound Pith citation observations are available.