Paper Citation Record · LEDGER

GL-ICNN: An End-To-End Interpretable Convolutional Neural Network for the Diagnosis and Prediction of Alzheimer's Disease

As of 21 August 2026, this Paper Citation Record lists 16 of 16 outbound references and 0 inbound Pith citation observations for arXiv:2501.11715.

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

pith.paper-citation-record.v1
2501.11715 v1

Coverage vector

measured 16 of 16 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T17:59:15.557166Z

measured 16 of 16 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+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

16 of 16 outbound references displayed

verified exact1
verified fuzzy13
unresolved2
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation ee7823dd-cf94-49f6-825c-b29dc9c695b6 · outbound

This paper cites Brain imaging in differential diagnosis of dementia,.

GL-ICNN: An End-To-End Interpretable Convolutional Neural Network for the Diagnosis and Prediction of Alzheimer's Disease Brain imaging in differential diagnosis of dementia,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:59:15.850716Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 83ca3151-def2-4a5e-9ee5-3d6418d94756 · outbound

This paper cites Convolutional neural networks for classification of Alzheimer’s disease: Overview and reproducible evaluation,.

GL-ICNN: An End-To-End Interpretable Convolutional Neural Network for the Diagnosis and Prediction of Alzheimer's Disease Convolutional neural networks for classification of Alzheimer’s disease: Overview and reproducible evaluation,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:59:15.834479Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 29b5c778-7518-4e13-8cbe-db1a70617a60 · outbound

This paper cites Interpretable machine learning for dementia: a systematic review,.

GL-ICNN: An End-To-End Interpretable Convolutional Neural Network for the Diagnosis and Prediction of Alzheimer's Disease Interpretable machine learning for dementia: a systematic review,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:59:15.817120Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 0748ca1b-6570-462f-8a5a-2c08a6fc8289 · outbound

This paper cites Challenges of implementing computer-aided diagnostic models for neuroimages in a clinical setting,.

GL-ICNN: An End-To-End Interpretable Convolutional Neural Network for the Diagnosis and Prediction of Alzheimer's Disease Challenges of implementing computer-aided diagnostic models for neuroimages in a clinical setting,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:59:15.800629Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation a8f197d8-42ca-41be-afab-167848bb2d56 · outbound

This paper cites Explainable Artificial Intelligence (XAI): Concepts, taxonomies, op- portunities and challenges toward responsible AI,.

GL-ICNN: An End-To-End Interpretable Convolutional Neural Network for the Diagnosis and Prediction of Alzheimer's Disease Explainable Artificial Intelligence (XAI): Concepts, taxonomies, op- portunities and challenges toward responsible AI,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:59:15.782932Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation f87a4f4f-3853-4018-a977-cb9370c0fbaa · outbound

This paper cites The (un) reliability of saliency methods,.

GL-ICNN: An End-To-End Interpretable Convolutional Neural Network for the Diagnosis and Prediction of Alzheimer's Disease The (un) reliability of saliency methods,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:59:15.767403Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 195ca1df-8806-4575-a92e-776b3190e888 · outbound

This paper cites Intelligible models for classification and regression,.

GL-ICNN: An End-To-End Interpretable Convolutional Neural Network for the Diagnosis and Prediction of Alzheimer's Disease Intelligible models for classification and regression,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:59:15.751510Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 745b417f-a0a5-4d38-8ae3-af335af16bd8 · outbound

This paper cites An Interpretable Machine Learning Model with Deep Learning-based Imaging Biomarkers for Diagnosis of Alzheimer's Disease.

GL-ICNN: An End-To-End Interpretable Convolutional Neural Network for the Diagnosis and Prediction of Alzheimer's Disease An Interpretable Machine Learning Model with Deep Learning-based Imaging Biomarkers for Diagnosis of Alzheimer's Disease

Reference 8

Resolution: verified exact; local_arxiv, observed 2026-08-10T17:59:15.622215Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation aabb3b9e-5d9b-4c8c-b79a-f70c8dcd6ed8 · outbound

This paper cites Densely connected convolutional networks,.

GL-ICNN: An End-To-End Interpretable Convolutional Neural Network for the Diagnosis and Prediction of Alzheimer's Disease Densely connected convolutional networks,

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-10T17:59:15.523099Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2a5ef1cc-2e9f-4cac-82dd-c4a69db9a38d · outbound

This paper cites Very Deep Convolutional Networks for Large-Scale Image Recognition.

GL-ICNN: An End-To-End Interpretable Convolutional Neural Network for the Diagnosis and Prediction of Alzheimer's Disease Very Deep Convolutional Networks for Large-Scale Image Recognition

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-10T17:59:15.528539Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6d35e329-7097-46ce-a237-2d05e069255b · outbound

This paper cites Intelligible models for healthcare: Predicting pneumonia risk and hospital 30-day readmission,.

GL-ICNN: An End-To-End Interpretable Convolutional Neural Network for the Diagnosis and Prediction of Alzheimer's Disease Intelligible models for healthcare: Predicting pneumonia risk and hospital 30-day readmission,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:59:15.725843Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 6c730e70-3c9a-4efc-9a46-373676bb623b · outbound

This paper cites Accuracy, interpretability, and differential privacy via explainable boosting,.

GL-ICNN: An End-To-End Interpretable Convolutional Neural Network for the Diagnosis and Prediction of Alzheimer's Disease Accuracy, interpretability, and differential privacy via explainable boosting,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:59:15.708010Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 2cadf1f6-3666-457e-aed4-cf8d6f708ab7 · outbound

This paper cites The Parelsnoer Institute: a national network of standardized clinical biobanks in the Netherlands,.

GL-ICNN: An End-To-End Interpretable Convolutional Neural Network for the Diagnosis and Prediction of Alzheimer's Disease The Parelsnoer Institute: a national network of standardized clinical biobanks in the Netherlands,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:59:15.691424Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 3ef5d45f-b977-4706-8f23-f777a2dae7b0 · outbound

This paper cites Cross-cohort generalizability of deep and conventional machine learn- ing for MRI-based diagnosis and prediction of Alzheimer’s disease,.

GL-ICNN: An End-To-End Interpretable Convolutional Neural Network for the Diagnosis and Prediction of Alzheimer's Disease Cross-cohort generalizability of deep and conventional machine learn- ing for MRI-based diagnosis and prediction of Alzheimer’s disease,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:59:15.674094Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation dd38f6af-3a27-4087-9f06-f22a8cfe075a · outbound

This paper cites Three-dimensional maximum probability atlas of the human brain, with particular reference to the temporal lobe,.

GL-ICNN: An End-To-End Interpretable Convolutional Neural Network for the Diagnosis and Prediction of Alzheimer's Disease Three-dimensional maximum probability atlas of the human brain, with particular reference to the temporal lobe,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:59:15.657103Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation f78fafaa-35b2-41e3-b5e5-faf2b9e3a7af · outbound

This paper cites Towards a biological definition of Alzheimer disease,.

GL-ICNN: An End-To-End Interpretable Convolutional Neural Network for the Diagnosis and Prediction of Alzheimer's Disease Towards a biological definition of Alzheimer disease,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:59:15.640875Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Pith citing papers

No inbound Pith citation observations are available.