Paper Citation Record · LEDGER

Deep Learning Approach for Enhancing Oral Squamous Cell Carcinoma with LIME Explainable AI Technique

As of 12 August 2026, this Paper Citation Record lists 15 of 15 outbound references and 1 inbound Pith citation observation for arXiv:2411.14184.

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

pith.paper-citation-record.v1
2411.14184 v2

Coverage vector

measured 15 of 15 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T15:31:35.165891Z

measured 16 of 16 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T23:05:42.361435Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-11T23:05:42.454446Z

Reference resolution

15 of 15 outbound references displayed

verified exact1
verified fuzzy13
unresolved1
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation da471669-a5be-49f1-8aa0-c1311f3b4cfc · outbound

This paper cites Oral cancer detection using transfer learning-based framework from histopathology images,.

Deep Learning Approach for Enhancing Oral Squamous Cell Carcinoma with LIME Explainable AI Technique Oral cancer detection using transfer learning-based framework from histopathology images,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:31:35.350039Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 6922b9bd-bab9-4bef-9338-9710c2cc5b96 · outbound

This paper cites Intelligent deep learning enabled oral squamous cell carcinoma detection and classification using biomedical images,.

Deep Learning Approach for Enhancing Oral Squamous Cell Carcinoma with LIME Explainable AI Technique Intelligent deep learning enabled oral squamous cell carcinoma detection and classification using biomedical images,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:31:35.338857Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 7ec6f429-9524-45b1-b146-fe15ee9013db · outbound

This paper cites Automated classification of cells into multiple classes in epithelial tissue of oral squamous cell carcinoma using transfer learning and convolutional neural network,.

Deep Learning Approach for Enhancing Oral Squamous Cell Carcinoma with LIME Explainable AI Technique Automated classification of cells into multiple classes in epithelial tissue of oral squamous cell carcinoma using transfer learning and convolutional neural network,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:31:35.328727Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 18b3f159-5834-4c65-9394-675fea2ef192 · outbound

This paper cites AI-based analysis of oral lesions using novel deep convolutional neural networks for early detection of oral cancer,.

Deep Learning Approach for Enhancing Oral Squamous Cell Carcinoma with LIME Explainable AI Technique AI-based analysis of oral lesions using novel deep convolutional neural networks for early detection of oral cancer,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:31:35.318471Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 6c1d6f37-951f-4505-83df-8739f27d4c8f · outbound

This paper cites Capsule network based analysis of histopathological images of oral squamous cell carcinoma,.

Deep Learning Approach for Enhancing Oral Squamous Cell Carcinoma with LIME Explainable AI Technique Capsule network based analysis of histopathological images of oral squamous cell carcinoma,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:31:35.307789Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation bd794227-996a-438c-aed2-323b5be62f3e · outbound

This paper cites Early diagnosis of oral cancer using image processing and artificial intelligence,.

Deep Learning Approach for Enhancing Oral Squamous Cell Carcinoma with LIME Explainable AI Technique Early diagnosis of oral cancer using image processing and artificial intelligence,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:31:35.297240Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 73a61d85-7ec9-4f8b-8b2c-031777b4039a · outbound

This paper cites Current insights into oral cancer diagnostics,.

Deep Learning Approach for Enhancing Oral Squamous Cell Carcinoma with LIME Explainable AI Technique Current insights into oral cancer diagnostics,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:31:35.287040Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 3b77bfb3-f74b-4e18-ba27-1444e49c3985 · outbound

This paper cites Automated detection and classification of oral lesions using deep learning for early detection of oral cancer,.

Deep Learning Approach for Enhancing Oral Squamous Cell Carcinoma with LIME Explainable AI Technique Automated detection and classification of oral lesions using deep learning for early detection of oral cancer,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:31:35.276494Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation b258a70c-0a35-4283-b256-387df1fd6a5d · outbound

This paper cites A novel lightweight deep convolutional neural network for early detection of oral cancer,.

Deep Learning Approach for Enhancing Oral Squamous Cell Carcinoma with LIME Explainable AI Technique A novel lightweight deep convolutional neural network for early detection of oral cancer,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:31:35.265236Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 0ddad249-d720-485e-a5be-d217ed6dd0c6 · outbound

This paper cites Multi-method analysis of histopathological image for early diagnosis of oral squamous cell carcinoma using deep learning and hybrid techniques,.

Deep Learning Approach for Enhancing Oral Squamous Cell Carcinoma with LIME Explainable AI Technique Multi-method analysis of histopathological image for early diagnosis of oral squamous cell carcinoma using deep learning and hybrid techniques,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:31:35.252970Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 1848feb3-fbae-4329-a605-6e4c7ba07fe0 · outbound

This paper cites Transfer Learning for Oral Cancer Detection using Microscopic Images.

Deep Learning Approach for Enhancing Oral Squamous Cell Carcinoma with LIME Explainable AI Technique Transfer Learning for Oral Cancer Detection using Microscopic Images

Reference 11

Resolution: verified exact; local_arxiv, observed 2026-08-12T15:31:35.208332Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 504b614f-3a7c-4e06-ae1a-e2ecf5104b40 · outbound

This paper cites Histopatho- logical imaging database for oral cancer analysis,.

Deep Learning Approach for Enhancing Oral Squamous Cell Carcinoma with LIME Explainable AI Technique Histopatho- logical imaging database for oral cancer analysis,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:31:35.241179Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 7ce388a6-061a-47c6-95d9-59f94623be01 · outbound

This paper cites Histopathologic oral cancer detection us- ing cnns,.

Deep Learning Approach for Enhancing Oral Squamous Cell Carcinoma with LIME Explainable AI Technique Histopathologic oral cancer detection us- ing cnns,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:31:35.230165Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 457e5bca-ce51-4a97-8323-aad0e494d736 · outbound

This paper cites Advance Transfer Learning Approach for Identification of Multiclass Skin Disease with LIME Explainable AI Technique,.

Deep Learning Approach for Enhancing Oral Squamous Cell Carcinoma with LIME Explainable AI Technique Advance Transfer Learning Approach for Identification of Multiclass Skin Disease with LIME Explainable AI Technique,

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-12T15:31:35.162469Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5e5f37d1-dc5f-4cb4-8155-1005bdc56a95 · outbound

This paper cites Optimizing Stroke Detection: An Analysis of Different Feature Selection Approaches,.

Deep Learning Approach for Enhancing Oral Squamous Cell Carcinoma with LIME Explainable AI Technique Optimizing Stroke Detection: An Analysis of Different Feature Selection Approaches,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:31:35.219561Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Pith citing papers

Observation 65be8aec-5d3c-4e90-9bb9-108b8b59e0d2 · inbound

Optimized IoT Intrusion Detection using Machine Learning Technique cites this paper.

Optimized IoT Intrusion Detection using Machine Learning Technique Deep Learning Approach for Enhancing Oral Squamous Cell Carcinoma with LIME Explainable AI Technique

Reference 13

Resolution: verified exact; local_arxiv, observed 2026-08-11T23:05:42.464739Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.