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Paper Citation Record · LEDGER

Self-eXplainable AI for Medical Image Analysis: A Survey and New Outlooks

As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2410.02331.

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

pith.paper-citation-record.v1
2410.02331 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 8 of 8 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T20:57:20.935951Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-20T10:13:11.857540Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 4a8ab5b4-d516-42e1-951d-5d6cb38d3d06 · inbound

Neural Probabilistic Circuits: Enabling Compositional and Interpretable Predictions through Logical Reasoning cites this paper.

Neural Probabilistic Circuits: Enabling Compositional and Interpretable Predictions through Logical Reasoning Self-eXplainable AI for Medical Image Analysis: A Survey and New Outlooks

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-10T20:57:20.935951Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T20:57:20.935951Z digest=sha256:24c55dc3cf5533c35facfea27f43b75da86eeba1d8aa849931a0d8441e473be3

Observation 031b3342-ace7-4e2a-bfb0-62304f324707 · inbound

An Explainable Biomedical Foundation Model via Large-Scale Concept-Enhanced Vision-Language Pre-training cites this paper.

An Explainable Biomedical Foundation Model via Large-Scale Concept-Enhanced Vision-Language Pre-training Self-eXplainable AI for Medical Image Analysis: A Survey and New Outlooks

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-10T14:13:32.044702Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:13:32.044702Z digest=sha256:cadba45253640938a8151d7fff82ab1057b6f9b31276e556a4605d37c536fbdf

Observation 12e4c531-5085-4fe3-b35b-1d37450ffbfc · inbound

MVP-CBM:Multi-layer Visual Preference-enhanced Concept Bottleneck Model for Explainable Medical Image Classification cites this paper.

MVP-CBM:Multi-layer Visual Preference-enhanced Concept Bottleneck Model for Explainable Medical Image Classification Self-eXplainable AI for Medical Image Analysis: A Survey and New Outlooks

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-07T00:49:51.013715Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T00:49:51.013715Z digest=sha256:550f8e0f568c26949c063304ca630598a2162792d15dc83aeebd21e1c56dda75

Observation 7eeae1f6-43bc-4acc-a167-5b0d7004050e · inbound

Segment Anything in Pathology Images with Natural Language cites this paper.

Segment Anything in Pathology Images with Natural Language Self-eXplainable AI for Medical Image Analysis: A Survey and New Outlooks

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-06T22:42:11.749811Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:42:11.749811Z digest=sha256:5c5c6f0c25422cec012783fe703adb00f24a525120b5c8d921f62b6645cde21b

Observation 2fccdeb4-8804-4574-bab4-80d831e173a0 · inbound

A Versatile Pathology Co-pilot via Reasoning Enhanced Multimodal Large Language Model cites this paper.

A Versatile Pathology Co-pilot via Reasoning Enhanced Multimodal Large Language Model Self-eXplainable AI for Medical Image Analysis: A Survey and New Outlooks

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-06T14:55:44.636105Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T14:55:44.636105Z digest=sha256:2e5e371b958dbe4265cf98b6ba0f56e6d3aa19b9f0100783cf9ceeeab433cac6

Observation 2c9db953-63da-464e-a326-b83740ff6747 · inbound

Solutions for Mitotic Figure Detection and Atypical Classification in MIDOG 2025 cites this paper.

Solutions for Mitotic Figure Detection and Atypical Classification in MIDOG 2025 Self-eXplainable AI for Medical Image Analysis: A Survey and New Outlooks

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-05T14:04:45.935553Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T14:04:45.935553Z digest=sha256:8a5db70206b31374fd5f843911615c99b510368e56df33524908add2a8e2709e

Observation 8287f62d-451a-43ba-b324-932bd5a05607 · inbound

Exploring Radiologists' Expectations of Explainable Machine Learning Models in Medical Image Analysis cites this paper.

Exploring Radiologists' Expectations of Explainable Machine Learning Models in Medical Image Analysis Self-eXplainable AI for Medical Image Analysis: A Survey and New Outlooks

Reference 9

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T11:16:10.604366Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-05-10T15:02:13.951049Z digest=sha256:dc8d9a7cade411278296a2b1d41d768d16e596be5cf5d67c12554158b6de98e2

Observation 4ac8f3c0-9e3b-42b1-9d78-eff30e2e5604 · inbound

Learning Quantifiable Visual Explanations Without Ground-Truth cites this paper.

Learning Quantifiable Visual Explanations Without Ground-Truth Self-eXplainable AI for Medical Image Analysis: A Survey and New Outlooks

Reference 55

Resolution
verified exact
arxiv_id, observed 2026-05-20T10:13:11.859800Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-05-20T10:11:48.674949Z digest=sha256:7be474311fd0707e9c516cf4a67f582af01ba985be7634bd33a2fe3753e33de3