Paper Citation Record · LEDGER

Improving Diagnostic Accuracy of Pigmented Skin Lesions With CNNs: an Application on the DermaMNIST Dataset

As of 7 August 2026, this Paper Citation Record lists 23 of 23 outbound references and 0 inbound Pith citation observations for arXiv:2507.12961.

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

pith.paper-citation-record.v1
2507.12961 v1

Coverage vector

measured 23 of 23 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T16:38:12.640219Z

measured 23 of 23 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+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

23 of 23 outbound references displayed

verified exact1
verified fuzzy17
unresolved5
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 5c7467a6-6285-443f-abef-b27092c09a29 · outbound

This paper cites Dermatoscopy,.

Improving Diagnostic Accuracy of Pigmented Skin Lesions With CNNs: an Application on the DermaMNIST Dataset Dermatoscopy,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:38:16.847424Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 55703db5-be47-4037-89c4-66ca05a4a88d · outbound

This paper cites an unresolved cited work.

Improving Diagnostic Accuracy of Pigmented Skin Lesions With CNNs: an Application on the DermaMNIST Dataset Unresolved cited work

Reference 2

Resolution: unresolved; raw_fallback, observed 2026-08-06T16:38:16.716613Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 2d9e9b02-55ef-4f04-9625-a65a21656ed7 · outbound

This paper cites an unresolved cited work.

Improving Diagnostic Accuracy of Pigmented Skin Lesions With CNNs: an Application on the DermaMNIST Dataset Unresolved cited work

Reference 3

Resolution: unresolved; raw_fallback, observed 2026-08-06T16:38:16.605805Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation e149ee2e-9a32-4d8c-a29b-6144c160b7e9 · outbound

This paper cites Current and future trends in molecular biomarkers for diagnostic, prognostic, and predictive purposes in non-melanoma skin cancer,.

Improving Diagnostic Accuracy of Pigmented Skin Lesions With CNNs: an Application on the DermaMNIST Dataset Current and future trends in molecular biomarkers for diagnostic, prognostic, and predictive purposes in non-melanoma skin cancer,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:38:16.453093Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 62d2ece1-6a5a-4cf8-9007-bfcfa5121e98 · outbound

This paper cites an unresolved cited work.

Improving Diagnostic Accuracy of Pigmented Skin Lesions With CNNs: an Application on the DermaMNIST Dataset Unresolved cited work

Reference 5

Resolution: unresolved; raw_fallback, observed 2026-08-06T16:38:16.337861Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 1815e218-cafc-4522-bc0d-81cb30c5ab89 · outbound

This paper cites an unresolved cited work.

Improving Diagnostic Accuracy of Pigmented Skin Lesions With CNNs: an Application on the DermaMNIST Dataset Unresolved cited work

Reference 6

Resolution: unresolved; raw_fallback, observed 2026-08-06T16:38:16.208358Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 1c3332ca-23d5-446e-86f2-8f0e96f12104 · outbound

This paper cites A gan-based image synthe- sis method for skin lesion classification,.

Improving Diagnostic Accuracy of Pigmented Skin Lesions With CNNs: an Application on the DermaMNIST Dataset A gan-based image synthe- sis method for skin lesion classification,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:38:16.089606Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 66827fbb-e9bd-44d7-a2ff-9dfa55924253 · outbound

This paper cites Medmnist v2-a large-scale lightweight benchmark for 2d and 3d biomedical image classification,.

Improving Diagnostic Accuracy of Pigmented Skin Lesions With CNNs: an Application on the DermaMNIST Dataset Medmnist v2-a large-scale lightweight benchmark for 2d and 3d biomedical image classification,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:38:15.828128Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 320cf48b-d60d-4798-ab10-0cf7fa523eaf · outbound

This paper cites The HAM10000 dataset, a large collection of multi-source dermatoscopic images of common pigmented skin lesions,.

Improving Diagnostic Accuracy of Pigmented Skin Lesions With CNNs: an Application on the DermaMNIST Dataset The HAM10000 dataset, a large collection of multi-source dermatoscopic images of common pigmented skin lesions,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:38:15.463068Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 931e4633-5bae-4145-9a2a-03cea83d8abb · outbound

This paper cites Applications of support vector machine (svm) learning in cancer genomics,.

Improving Diagnostic Accuracy of Pigmented Skin Lesions With CNNs: an Application on the DermaMNIST Dataset Applications of support vector machine (svm) learning in cancer genomics,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:38:15.272611Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation e8fb9738-43fe-46fb-a3a0-0db82a122d49 · outbound

This paper cites Medmnist classification decathlon: A lightweight automl benchmark for medical image analysis,.

Improving Diagnostic Accuracy of Pigmented Skin Lesions With CNNs: an Application on the DermaMNIST Dataset Medmnist classification decathlon: A lightweight automl benchmark for medical image analysis,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:38:15.069642Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 79e6c69e-c35f-4349-84f3-800899a613b9 · outbound

This paper cites The ham10000 dataset, a large collection of multi-source dermatoscopic images of common pigmented skin lesions,.

Improving Diagnostic Accuracy of Pigmented Skin Lesions With CNNs: an Application on the DermaMNIST Dataset The ham10000 dataset, a large collection of multi-source dermatoscopic images of common pigmented skin lesions,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:38:14.872344Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 7a71594e-1a1d-4fe1-a569-165e0a29299a · outbound

This paper cites Skin Lesion Analysis Toward Melanoma Detection 2018: A Challenge Hosted by the International Skin Imaging Collaboration (ISIC).

Improving Diagnostic Accuracy of Pigmented Skin Lesions With CNNs: an Application on the DermaMNIST Dataset Skin Lesion Analysis Toward Melanoma Detection 2018: A Challenge Hosted by the International Skin Imaging Collaboration (ISIC)

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-06T16:38:11.673398Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation edf4edd7-671d-4b40-907b-8c3291fd1e17 · outbound

This paper cites Investigating the quality of dermamnist and fitzpatrick17k dermatological image datasets,.

Improving Diagnostic Accuracy of Pigmented Skin Lesions With CNNs: an Application on the DermaMNIST Dataset Investigating the quality of dermamnist and fitzpatrick17k dermatological image datasets,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:38:14.688879Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 92d5289f-6a94-4982-9d68-d2c29a0c4e63 · outbound

This paper cites Unsupervised method for wildfire flame segmen- tation and detection,.

Improving Diagnostic Accuracy of Pigmented Skin Lesions With CNNs: an Application on the DermaMNIST Dataset Unsupervised method for wildfire flame segmen- tation and detection,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:38:14.489424Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation a624c82e-d8f5-45fe-9654-4bab6d9af6b8 · outbound

This paper cites A review on evaluation metrics for data classification evaluations,.

Improving Diagnostic Accuracy of Pigmented Skin Lesions With CNNs: an Application on the DermaMNIST Dataset A review on evaluation metrics for data classification evaluations,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:38:14.356235Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 093a9f98-a7f6-46a5-8bc1-191561f3e077 · outbound

This paper cites Hybrid learning of hand-crafted and deep-activated features using particle swarm optimization and optimized support vector machine for tuberculosis screening,.

Improving Diagnostic Accuracy of Pigmented Skin Lesions With CNNs: an Application on the DermaMNIST Dataset Hybrid learning of hand-crafted and deep-activated features using particle swarm optimization and optimized support vector machine for tuberculosis screening,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:38:14.207848Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 1e544205-f91e-4c1d-816c-f23cbef07796 · outbound

This paper cites Attentive octave convolutional capsule network for medical image classification,.

Improving Diagnostic Accuracy of Pigmented Skin Lesions With CNNs: an Application on the DermaMNIST Dataset Attentive octave convolutional capsule network for medical image classification,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:38:13.891487Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation b1a92af6-1369-4043-a1e2-3cb0a10fb28f · outbound

This paper cites Extreme learning machine for biomedical image classification: A multi- case study,.

Improving Diagnostic Accuracy of Pigmented Skin Lesions With CNNs: an Application on the DermaMNIST Dataset Extreme learning machine for biomedical image classification: A multi- case study,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:38:13.717800Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 3de60650-d349-470d-bc99-5566bcc254c7 · outbound

This paper cites Skin lesion clas- sification based on hybrid self-supervised pretext task,.

Improving Diagnostic Accuracy of Pigmented Skin Lesions With CNNs: an Application on the DermaMNIST Dataset Skin lesion clas- sification based on hybrid self-supervised pretext task,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:38:13.491484Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation b59b27a0-a00c-44db-8e41-da1cc545e2ab · outbound

This paper cites Medrdf: a robust and retrain-less diagnostic framework for medical pretrained models against adversarial attack,.

Improving Diagnostic Accuracy of Pigmented Skin Lesions With CNNs: an Application on the DermaMNIST Dataset Medrdf: a robust and retrain-less diagnostic framework for medical pretrained models against adversarial attack,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:38:13.293081Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 32993f49-41b4-4ba0-a25f-fc504067de7c · outbound

This paper cites Failure detection in deep neural networks for medical imaging,.

Improving Diagnostic Accuracy of Pigmented Skin Lesions With CNNs: an Application on the DermaMNIST Dataset Failure detection in deep neural networks for medical imaging,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:38:13.084646Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 8d717591-016c-4c30-bc69-a0000ff61c6e · outbound

This paper cites Deeply Supervised Layer Selective Attention Network: Towards Label-Efficient Learning for Medical Image Classification.

Improving Diagnostic Accuracy of Pigmented Skin Lesions With CNNs: an Application on the DermaMNIST Dataset Deeply Supervised Layer Selective Attention Network: Towards Label-Efficient Learning for Medical Image Classification

Reference 23

Resolution: verified exact; local_arxiv, observed 2026-08-06T16:38:12.858229Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Pith citing papers

No inbound Pith citation observations are available.