Paper Citation Record · LEDGER

Pitfalls of Conformal Predictions for Medical Image Classification

As of 8 August 2026, this Paper Citation Record lists 23 of 23 outbound references and 0 inbound Pith citation observations for arXiv:2506.18162.

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

pith.paper-citation-record.v1
2506.18162 v1

Coverage vector

measured 23 of 23 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T23:27:18.322915Z

measured 23 of 23 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+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 exact4
verified fuzzy4
unresolved14
parse uncertain0
malformed identifier0
metadata mismatch1

External citation measurements

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Outbound references

Observation 362343af-c0c3-4182-9fd1-e05be96ef2dc · outbound

This paper cites The need for uncertainty quantification in machine-assisted medical decision making.

Pitfalls of Conformal Predictions for Medical Image Classification The need for uncertainty quantification in machine-assisted medical decision making

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-06T23:27:16.523678Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cb305aa5-6c9e-468a-89b2-4ae66459407e · outbound

This paper cites Deep learning in histopathology: the path to the clinic.

Pitfalls of Conformal Predictions for Medical Image Classification Deep learning in histopathology: the path to the clinic

Reference 2

Resolution: verified exact; doi, observed 2026-08-06T23:27:18.704163Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 192feb7e-9f57-47fc-a6c2-0aa0a50a7c53 · outbound

This paper cites Second opinion needed: communicating uncertainty in medical machine learning.

Pitfalls of Conformal Predictions for Medical Image Classification Second opinion needed: communicating uncertainty in medical machine learning

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-06T23:27:16.745482Z

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Observation f0e4f3e2-cc26-4052-85bc-1901d238a7b6 · outbound

This paper cites A Call to Reflect on Evaluation Practices for Failure Detection in Image Classification.

Pitfalls of Conformal Predictions for Medical Image Classification A Call to Reflect on Evaluation Practices for Failure Detection in Image Classification

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-06T23:27:16.868550Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 390250f9-cf7a-4af3-ba06-16d6bc85f31f · outbound

This paper cites Benchmarking common uncertainty estimation methods with histopathological images under domain shift and label noise.

Pitfalls of Conformal Predictions for Medical Image Classification Benchmarking common uncertainty estimation methods with histopathological images under domain shift and label noise

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-06T23:27:16.955718Z

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Observation 09d9c10e-e374-418a-b44b-e9ab3a065895 · outbound

This paper cites an unresolved cited work.

Pitfalls of Conformal Predictions for Medical Image Classification Unresolved cited work

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-06T23:27:17.034550Z

Source-reported events for the cited work

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Observation 52595aee-669e-4f4f-9b42-b5628d861a4c · outbound

This paper cites Deep learning with conformal prediction for hierarchical analysis of large-scale whole-slide tissue images.

Pitfalls of Conformal Predictions for Medical Image Classification Deep learning with conformal prediction for hierarchical analysis of large-scale whole-slide tissue images

Reference 7

Resolution: metadata mismatch; raw_fallback, observed 2026-08-06T23:27:18.943108Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 50e1e913-88b3-4832-9367-1fbf7cc65b27 · outbound

This paper cites Estimating diagnostic uncertainty in artificial intelligence assisted pathology using confor- mal prediction.

Pitfalls of Conformal Predictions for Medical Image Classification Estimating diagnostic uncertainty in artificial intelligence assisted pathology using confor- mal prediction

Reference 8

Resolution: verified exact; doi, observed 2026-08-06T23:27:18.672063Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 7ca5935b-93fb-41ee-a671-bc1ca22f833d · outbound

This paper cites Fair conformal predictors for applications in medical imaging.

Pitfalls of Conformal Predictions for Medical Image Classification Fair conformal predictors for applications in medical imaging

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-06T23:27:17.250854Z

Source-reported events for the cited work

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Observation 1ba1e993-205d-4048-9a0c-54f185b168bc · outbound

This paper cites Three Applications of Conformal Prediction for Rating Breast Density in Mammography.

Pitfalls of Conformal Predictions for Medical Image Classification Three Applications of Conformal Prediction for Rating Breast Density in Mammography

Reference 10

Resolution: verified exact; local_arxiv, observed 2026-08-06T23:27:18.653518Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 2ab5b995-24a8-44fb-af61-d2a5c6054ee6 · outbound

This paper cites Improving Trustworthiness of AI Disease Severity Rating in Medical Imaging with Ordinal Conformal Prediction Sets.

Pitfalls of Conformal Predictions for Medical Image Classification Improving Trustworthiness of AI Disease Severity Rating in Medical Imaging with Ordinal Conformal Prediction Sets

Reference 11

Resolution: verified exact; local_arxiv, observed 2026-08-06T23:27:18.615719Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 6d6c0741-819b-456b-8a82-eb87fc754290 · outbound

This paper cites A Gentle Introduction to Conformal Prediction and Distribution-Free Uncertainty Quantification.

Pitfalls of Conformal Predictions for Medical Image Classification A Gentle Introduction to Conformal Prediction and Distribution-Free Uncertainty Quantification

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-06T23:27:17.412796Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c3bb5a60-4b57-4902-bc01-176475d58feb · outbound

This paper cites Selective classification for deep neural networks.

Pitfalls of Conformal Predictions for Medical Image Classification Selective classification for deep neural networks

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:27:19.057757Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 37ce6fe6-4cbd-420d-add5-9024b15e35f2 · outbound

This paper cites Classification with valid and adaptive coverage.

Pitfalls of Conformal Predictions for Medical Image Classification Classification with valid and adaptive coverage

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-06T23:27:17.539667Z

Source-reported events for the cited work

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Observation b9e6cabb-de97-4d32-a456-c0314c8fe415 · outbound

This paper cites Uncertainty Sets for Image Classifiers using Conformal Prediction.

Pitfalls of Conformal Predictions for Medical Image Classification Uncertainty Sets for Image Classifiers using Conformal Prediction

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-06T23:27:17.598136Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a68177f7-4b65-4f59-9f2f-933a1dc01c12 · outbound

This paper cites Deep residual learning for image recognition.

Pitfalls of Conformal Predictions for Medical Image Classification Deep residual learning for image recognition

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-06T23:27:17.658482Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a000d916-f86d-4da4-9a3f-5ff7053dda14 · outbound

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

Pitfalls of Conformal Predictions for Medical Image Classification The HAM10000 dataset, a large collection of multi- source dermatoscopic images of common pigmented skin lesions

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-06T23:27:17.726104Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b453ea8e-3179-4147-b0be-b7e32fd270d3 · outbound

This paper cites From detection of individual metastases to classification of lymph node status at the patient level: the camelyon17 challenge.

Pitfalls of Conformal Predictions for Medical Image Classification From detection of individual metastases to classification of lymph node status at the patient level: the camelyon17 challenge

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-06T23:27:17.791326Z

Source-reported events for the cited work

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Observation 49610ede-4515-4ea8-b8c0-9b3827d7be61 · outbound

This paper cites Simple and scalable predictive uncertainty estimation using deep ensembles.

Pitfalls of Conformal Predictions for Medical Image Classification Simple and scalable predictive uncertainty estimation using deep ensembles

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:27:19.038542Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 58577d73-e4ff-4bc6-9343-1235870d0658 · outbound

This paper cites Dropout as a bayesian approximation: Representing model uncertainty in deep learning.

Pitfalls of Conformal Predictions for Medical Image Classification Dropout as a bayesian approximation: Representing model uncertainty in deep learning

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:27:19.025347Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation a55f3bed-5d3f-4ffc-a9aa-c72412ad06f8 · outbound

This paper cites A simple baseline for bayesian uncertainty in deep learning.

Pitfalls of Conformal Predictions for Medical Image Classification A simple baseline for bayesian uncertainty in deep learning

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:27:19.012671Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 3e7c92e0-baca-40ec-b829-d064bc659cba · outbound

This paper cites Conditional validity of inductive conformal predictors.

Pitfalls of Conformal Predictions for Medical Image Classification Conditional validity of inductive conformal predictors

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-06T23:27:18.149545Z

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Observation 7eeef12a-5844-4784-908b-bb09ec44caf4 · outbound

This paper cites Imagenet: A large-scale hierarchical image database.

Pitfalls of Conformal Predictions for Medical Image Classification Imagenet: A large-scale hierarchical image database

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-06T23:27:18.322915Z

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Pith citing papers

No inbound Pith citation observations are available.