Paper Citation Record · LEDGER

Improving Generalization in MRI-Based Deep Learning Models for Total Knee Replacement Prediction

As of 21 August 2026, this Paper Citation Record lists 29 of 29 outbound references and 0 inbound Pith citation observations for arXiv:2504.19203.

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

pith.paper-citation-record.v1
2504.19203 v7

Coverage vector

measured 29 of 29 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T06:04:22.939925Z

measured 29 of 29 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

29 of 29 outbound references displayed

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verified fuzzy3
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 69c03057-5199-4483-bcff-e8430c86dd1b · outbound

This paper cites Deep learning for knee osteoarthritis diagnosis and progression prediction from plain radiographs and clinical data,.

Improving Generalization in MRI-Based Deep Learning Models for Total Knee Replacement Prediction Deep learning for knee osteoarthritis diagnosis and progression prediction from plain radiographs and clinical data,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T06:04:23.416504Z

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 87b5547e-cfdb-4518-be47-b287fc322ceb · outbound

This paper cites Segmentation of knee bones for Osteoarthritis assessment: A comparative analysis of supervis ed, Few -Shot, and Zero -Shot learning approaches,.

Improving Generalization in MRI-Based Deep Learning Models for Total Knee Replacement Prediction Segmentation of knee bones for Osteoarthritis assessment: A comparative analysis of supervis ed, Few -Shot, and Zero -Shot learning approaches,

Reference 2

Resolution: verified exact; doi, observed 2026-08-16T06:04:23.188485Z

Source-reported events for the cited work

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Observation bb3001fb-14fc-4755-a196-717247102b93 · outbound

This paper cites A Progressive Risk Formulation for Enhanced Deep Learning based Total Knee Replacement Prediction in Knee Osteoarthritis.

Improving Generalization in MRI-Based Deep Learning Models for Total Knee Replacement Prediction A Progressive Risk Formulation for Enhanced Deep Learning based Total Knee Replacement Prediction in Knee Osteoarthritis

Reference 3

Resolution: verified exact; local_arxiv, observed 2026-08-16T06:04:23.177270Z

Source-reported events for the cited work

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Observation 0daa8364-8d9e-41f9-a516-f86fb5aa29d3 · outbound

This paper cites Discovering knee osteoarthritis imaging features for diagnosis and prognosis: Review of manual imaging grading and machine learning approaches,.

Improving Generalization in MRI-Based Deep Learning Models for Total Knee Replacement Prediction Discovering knee osteoarthritis imaging features for diagnosis and prognosis: Review of manual imaging grading and machine learning approaches,

Reference 4

Resolution: verified exact; doi, observed 2026-08-16T06:04:23.162592Z

Source-reported events for the cited work

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Observation 48161a23-c469-41c1-b754-14da21b44ddb · outbound

This paper cites Imaging of knee osteoarthritis: a review of multimodal diagnostic appr oach,.

Improving Generalization in MRI-Based Deep Learning Models for Total Knee Replacement Prediction Imaging of knee osteoarthritis: a review of multimodal diagnostic appr oach,

Reference 5

Resolution: verified exact; doi, observed 2026-08-16T06:04:23.151312Z

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 4a577f4b-f703-4894-b875-0802f504d1fe · outbound

This paper cites A deep learning method for predicting knee osteoarthritis radiographic progression from MR I,.

Improving Generalization in MRI-Based Deep Learning Models for Total Knee Replacement Prediction A deep learning method for predicting knee osteoarthritis radiographic progression from MR I,

Reference 6

Resolution: malformed identifier; doi_truncated, observed 2026-08-16T06:04:23.140651Z

Source-reported events for the cited work

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Observation c171a67a-8162-464e-a54e-0ec6d36d8a12 · outbound

This paper cites Deep Learning Predicts Total Knee Replacement from Magnetic Resonance Images,.

Improving Generalization in MRI-Based Deep Learning Models for Total Knee Replacement Prediction Deep Learning Predicts Total Knee Replacement from Magnetic Resonance Images,

Reference 7

Resolution: verified exact; doi, observed 2026-08-16T06:04:23.129625Z

Source-reported events for the cited work

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Observation 352d2d2f-24b2-41ad-8164-749b1bad570a · outbound

This paper cites Predicting Knee Osteoarthritis Progression from Structural MRI Using Deep Learning,.

Improving Generalization in MRI-Based Deep Learning Models for Total Knee Replacement Prediction Predicting Knee Osteoarthritis Progression from Structural MRI Using Deep Learning,

Reference 8

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Source-reported events for the cited work

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Observation dc257158-6ff0-4141-9518-b8af041586db · outbound

This paper cites Prediction of total knee replacement using deep learning analysis of knee MRI,.

Improving Generalization in MRI-Based Deep Learning Models for Total Knee Replacement Prediction Prediction of total knee replacement using deep learning analysis of knee MRI,

Reference 9

Resolution: verified exact; doi, observed 2026-08-16T06:04:23.117940Z

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 56ad31ee-4f91-425a-b6e7-9265e71f3be4 · outbound

This paper cites Unsupervised domain adaptation for automated knee osteoarthritis phenotype classification,.

Improving Generalization in MRI-Based Deep Learning Models for Total Knee Replacement Prediction Unsupervised domain adaptation for automated knee osteoarthritis phenotype classification,

Reference 10

Resolution: verified exact; doi, observed 2026-08-16T06:04:23.105940Z

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 95a87a16-dc5e-4d08-92a6-6e0e46b82458 · outbound

This paper cites Unsupervised Domain Adaptation by Backpropagation.

Improving Generalization in MRI-Based Deep Learning Models for Total Knee Replacement Prediction Unsupervised Domain Adaptation by Backpropagation

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-16T06:04:22.874089Z

Source-reported events for the cited work

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Observation efaf93f6-6932-4013-825f-74958bbf43a4 · outbound

This paper cites Deep Domain Confusion: Maximizing for Domain Invariance.

Improving Generalization in MRI-Based Deep Learning Models for Total Knee Replacement Prediction Deep Domain Confusion: Maximizing for Domain Invariance

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-16T06:04:22.878390Z

Source-reported events for the cited work

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Observation 576d7389-630a-4cab-b96a-789347666370 · outbound

This paper cites Domain Generalization via Invariant Feature Representation.

Improving Generalization in MRI-Based Deep Learning Models for Total Knee Replacement Prediction Domain Generalization via Invariant Feature Representation

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-16T06:04:22.882560Z

Source-reported events for the cited work

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Observation 5570b900-e646-49fb-8872-27bce2f80e78 · outbound

This paper cites Improved Regularization of Convolutional Neural Networks with Cutout.

Improving Generalization in MRI-Based Deep Learning Models for Total Knee Replacement Prediction Improved Regularization of Convolutional Neural Networks with Cutout

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-16T06:04:22.886329Z

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Observation 3f90b529-2f91-4985-bc7c-41ed4863ea7e · outbound

This paper cites MixStyle Neural Networks for Domain Generalization and Adaptation.

Improving Generalization in MRI-Based Deep Learning Models for Total Knee Replacement Prediction MixStyle Neural Networks for Domain Generalization and Adaptation

Reference 15

Resolution: verified exact; local_arxiv, observed 2026-08-16T06:04:23.074257Z

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 4dae5278-6d79-4a12-95c6-4dc36f78c970 · outbound

This paper cites Realistic Adversarial Data Augmentation for MR Image Segmentation.

Improving Generalization in MRI-Based Deep Learning Models for Total Knee Replacement Prediction Realistic Adversarial Data Augmentation for MR Image Segmentation

Reference 16

Resolution: verified exact; local_arxiv, observed 2026-08-16T06:04:23.059350Z

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 ff802b84-5c23-4d44-9e03-ba3c02a4bcfe · outbound

This paper cites Self-Challenging Improves Cross-Domain Generalization.

Improving Generalization in MRI-Based Deep Learning Models for Total Knee Replacement Prediction Self-Challenging Improves Cross-Domain Generalization

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-16T06:04:22.897962Z

Source-reported events for the cited work

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Observation e8ba72d8-54be-499f-8340-79934f65d2a0 · outbound

This paper cites Learning to optimize domain specific normalization for domain generalization,.

Improving Generalization in MRI-Based Deep Learning Models for Total Knee Replacement Prediction Learning to optimize domain specific normalization for domain generalization,

Reference 18

Resolution: verified exact; doi, observed 2026-08-16T06:04:23.034702Z

Source-reported events for the cited work

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Observation f4b6c8d6-5fab-4bba-be2b-25d30692536b · outbound

This paper cites Adversarially Adaptive Normalization for Single Domain Generalization.

Improving Generalization in MRI-Based Deep Learning Models for Total Knee Replacement Prediction Adversarially Adaptive Normalization for Single Domain Generalization

Reference 19

Resolution: verified exact; local_arxiv, observed 2026-08-16T06:04:23.023318Z

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 6d33305d-5114-45e4-b6d5-fa3d0c95f2d9 · outbound

This paper cites Causality -Inspired Single -Source domain generalization for medical image segmentation,.

Improving Generalization in MRI-Based Deep Learning Models for Total Knee Replacement Prediction Causality -Inspired Single -Source domain generalization for medical image segmentation,

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-16T06:04:22.909946Z

Source-reported events for the cited work

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Observation 55783419-ab94-455c-9fdc-edceafc24c68 · outbound

This paper cites Unsupervised MR harmonization by learning disentangled representations using information bottleneck theory,.

Improving Generalization in MRI-Based Deep Learning Models for Total Knee Replacement Prediction Unsupervised MR harmonization by learning disentangled representations using information bottleneck theory,

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-16T06:04:22.914382Z

Source-reported events for the cited work

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Observation 612e4916-5253-40ba-809a-2660a94dfb19 · outbound

This paper cites Disentangling a single MR modality,.

Improving Generalization in MRI-Based Deep Learning Models for Total Knee Replacement Prediction Disentangling a single MR modality,

Reference 22

Resolution: malformed identifier; no resolver link, observed 2026-08-16T06:04:22.917897Z

Source-reported events for the cited work

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Observation f0611e8e-8a07-4d27-8f69-b3d85745bc09 · outbound

This paper cites PyTorch Metric Learning.

Improving Generalization in MRI-Based Deep Learning Models for Total Knee Replacement Prediction PyTorch Metric Learning

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-16T06:04:22.921620Z

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Observation 98cf0834-1bfc-44fa-90c1-dd1c54b7cba2 · outbound

This paper cites Adversarial Consistency for Single Domain Generalization in Medical Image Segmentation,.

Improving Generalization in MRI-Based Deep Learning Models for Total Knee Replacement Prediction Adversarial Consistency for Single Domain Generalization in Medical Image Segmentation,

Reference 24

Resolution: verified exact; doi, observed 2026-08-16T06:04:22.990781Z

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 10108d3e-5eec-499b-bb2e-4d28779cabb1 · outbound

This paper cites Mixed Samples as Probes for Unsupervised Model Selection in Domain Adaptation,.

Improving Generalization in MRI-Based Deep Learning Models for Total Knee Replacement Prediction Mixed Samples as Probes for Unsupervised Model Selection in Domain Adaptation,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T06:04:23.395095Z

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 d333d6bb-a688-433e-8948-65946c99a4ee · outbound

This paper cites Minimal-Entropy Correlation Alignment for Unsupervised Deep Domain Adaptation.

Improving Generalization in MRI-Based Deep Learning Models for Total Knee Replacement Prediction Minimal-Entropy Correlation Alignment for Unsupervised Deep Domain Adaptation

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-16T06:04:22.932186Z

Source-reported events for the cited work

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Observation 4baee1b6-d413-4744-a6f3-a88cc725cacd · outbound

This paper cites Three New Validators and a Large-Scale Benchmark Ranking for Unsupervised Domain Adaptation.

Improving Generalization in MRI-Based Deep Learning Models for Total Knee Replacement Prediction Three New Validators and a Large-Scale Benchmark Ranking for Unsupervised Domain Adaptation

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-16T06:04:22.936139Z

Source-reported events for the cited work

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Observation f79d8805-69db-4680-8188-a335fb523138 · outbound

This paper cites Assessing Model Out- of-distribution Generalization with Softmax Prediction Probability Baselines and A Correlation Method,.

Improving Generalization in MRI-Based Deep Learning Models for Total Knee Replacement Prediction Assessing Model Out- of-distribution Generalization with Softmax Prediction Probability Baselines and A Correlation Method,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T06:04:23.384429Z

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 72d8062c-7491-4a98-a758-67dae928da91 · outbound

This paper cites an unresolved cited work.

Improving Generalization in MRI-Based Deep Learning Models for Total Knee Replacement Prediction Unresolved cited work

Reference 2020

Resolution: unresolved; raw_fallback, observed 2026-08-16T06:04:23.405464Z

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.