Paper Citation Record · LEDGER

An analysis of data variation and bias in image-based dermatological datasets for machine learning classification

As of 21 August 2026, this Paper Citation Record lists 21 of 21 outbound references and 1 inbound Pith citation observation for arXiv:2501.08962.

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

pith.paper-citation-record.v1
2501.08962 v2

Coverage vector

measured 21 of 21 reference resolution

Typed states for the displayed outbound observations.

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measured 22 of 22 standing notices

One-hop event checks from named stored sources.

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measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

21 of 21 outbound references displayed

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External citation measurements

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Outbound references

Observation 5ad432f7-d2e5-4d5d-8d92-6e0a5782816c · outbound

This paper cites BCN20000: Dermoscopic Lesions in the Wild.

An analysis of data variation and bias in image-based dermatological datasets for machine learning classification BCN20000: Dermoscopic Lesions in the Wild

Reference 1

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Observation 059d468c-458f-4055-9df9-5f007899bbcd · outbound

This paper cites JAMA dermatology157(11), 1362–1369 (2021).

An analysis of data variation and bias in image-based dermatological datasets for machine learning classification JAMA dermatology157(11), 1362–1369 (2021)

Reference 2

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Observation 7fba549c-d655-4344-881f-9966ae13c0b3 · outbound

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An analysis of data variation and bias in image-based dermatological datasets for machine learning classification Unresolved cited work

Reference 3

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Observation e41c698d-6cb3-4b75-926b-094cd68a0880 · outbound

This paper cites In: 2009 IEEE conference on computer vision and pattern recognition.

An analysis of data variation and bias in image-based dermatological datasets for machine learning classification In: 2009 IEEE conference on computer vision and pattern recognition

Reference 4

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Observation 168aabfe-7768-42b1-967f-92879dcece41 · outbound

This paper cites bmj 368 (2020).

An analysis of data variation and bias in image-based dermatological datasets for machine learning classification bmj 368 (2020)

Reference 5

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Observation a0d5552a-8ce7-49ed-8f76-62897f9d1d4f · outbound

This paper cites Expert systems with applications42(19), 6578–6585 (2015).

An analysis of data variation and bias in image-based dermatological datasets for machine learning classification Expert systems with applications42(19), 6578–6585 (2015)

Reference 6

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Observation 73802972-c838-4f9e-b2f2-d3b39f4f42c8 · outbound

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An analysis of data variation and bias in image-based dermatological datasets for machine learning classification Unresolved cited work

Reference 7

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Observation 6ac00274-7d68-4767-89c2-c07ae03b98a9 · outbound

This paper cites Computers in Biology and Medicine p.

An analysis of data variation and bias in image-based dermatological datasets for machine learning classification Computers in Biology and Medicine p

Reference 8

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Observation 6d9ed05a-e725-4483-bf19-2a0c5170fc80 · outbound

This paper cites In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition.

An analysis of data variation and bias in image-based dermatological datasets for machine learning classification In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition

Reference 9

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Observation 95df825c-dac9-41c4-a6f0-980e103cdefd · outbound

This paper cites Dermoscopy image analysis (2015).

An analysis of data variation and bias in image-based dermatological datasets for machine learning classification Dermoscopy image analysis (2015)

Reference 10

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Observation be57f86e-3baf-4485-8eab-1c013883240d · outbound

This paper cites Topical formulations.

An analysis of data variation and bias in image-based dermatological datasets for machine learning classification Topical formulations

Reference 11

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Observation 4e276517-f3dc-4097-aae3-73f9b99b8574 · outbound

This paper cites Data Brief32(106221), 106221 (Oct 2020).

An analysis of data variation and bias in image-based dermatological datasets for machine learning classification Data Brief32(106221), 106221 (Oct 2020)

Reference 12

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Observation 794756cb-f280-4a32-8d05-6cd0a02fce33 · outbound

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An analysis of data variation and bias in image-based dermatological datasets for machine learning classification Unresolved cited work

Reference 13

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Observation 6533a8d6-1c1e-4e03-a0a1-55f52eb866e9 · outbound

This paper cites Healthcare Analytics 3, 100143 (2023).

An analysis of data variation and bias in image-based dermatological datasets for machine learning classification Healthcare Analytics 3, 100143 (2023)

Reference 14

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Observation bc9cb665-a625-4879-98cc-f6c49f49bfd0 · outbound

This paper cites Computers in biology and medicine140, 105111 (2022).

An analysis of data variation and bias in image-based dermatological datasets for machine learning classification Computers in biology and medicine140, 105111 (2022)

Reference 15

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Observation b70abb30-6619-45c2-9e09-29f2876b5ec4 · outbound

This paper cites Biomedical Sig- nal Processing and Control 84, 104729 (2023).

An analysis of data variation and bias in image-based dermatological datasets for machine learning classification Biomedical Sig- nal Processing and Control 84, 104729 (2023)

Reference 16

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Observation ee78b303-5d6c-44fd-8f29-0fcaf58cb766 · outbound

This paper cites Journal of the American Academy of Dermatology55(1), 54–58 (2006).

An analysis of data variation and bias in image-based dermatological datasets for machine learning classification Journal of the American Academy of Dermatology55(1), 54–58 (2006)

Reference 17

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Observation 408273bd-e412-4eac-a4a6-449d57713d04 · outbound

This paper cites Scientific data 5(1), 1–9 (2018).

An analysis of data variation and bias in image-based dermatological datasets for machine learning classification Scientific data 5(1), 1–9 (2018)

Reference 18

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Observation e91607ca-4802-47c5-a243-fe38a9172629 · outbound

This paper cites Nature Medicine27(4), 582–584 (2021).

An analysis of data variation and bias in image-based dermatological datasets for machine learning classification Nature Medicine27(4), 582–584 (2021)

Reference 19

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Observation 13fa9bca-bf2b-481e-bfde-40e03123f1aa · outbound

This paper cites In: Information Processing in Medical Imaging: 26th International Confer- ence, IPMI 2019, Hong Kong, China, June 2–7, 2019, Proceedings 26.

An analysis of data variation and bias in image-based dermatological datasets for machine learning classification In: Information Processing in Medical Imaging: 26th International Confer- ence, IPMI 2019, Hong Kong, China, June 2–7, 2019, Proceedings 26

Reference 20

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Observation a4b19ca0-73c4-47b1-b7cf-bcac1a2be954 · outbound

This paper cites IEEE Access7, 9872–9880 (2019).

An analysis of data variation and bias in image-based dermatological datasets for machine learning classification IEEE Access7, 9872–9880 (2019)

Reference 21

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Pith citing papers

Observation 54618cde-f06a-4a01-b512-c186df6945a8 · inbound

Contrastive meta-domain adaptation for robust skin lesion classification across clinical and acquisition conditions cites this paper.

Contrastive meta-domain adaptation for robust skin lesion classification across clinical and acquisition conditions An analysis of data variation and bias in image-based dermatological datasets for machine learning classification

Reference 11

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