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Paper Citation Record · LEDGER

Robust Training with Data Augmentation for Medical Imaging Classification

As of 18 August 2026, this Paper Citation Record lists 29 of 29 outbound references and 0 inbound Pith citation observations for arXiv:2506.17133.

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

pith.paper-citation-record.v1
2506.17133 v1

Coverage vector

measured 29 of 29 reference resolution

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Source: paper_references, paper_reference_links, observed 2026-08-15T19:15:10.264798Z

measured 29 of 29 standing notices

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measured 0 of 0 inbound itemization

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Reference resolution

29 of 29 outbound references displayed

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External citation measurements

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Outbound references

Observation f2c3169a-c60a-41d1-b084-e7f310a7fd18 · outbound

This paper cites BMC bioinformatics 20, 1–20 (2019).

Robust Training with Data Augmentation for Medical Imaging Classification BMC bioinformatics 20, 1–20 (2019)

Reference 1

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Observation 1ec13cf0-ed38-420f-b528-d59f581895b5 · outbound

This paper cites Medical Physics 49(6), 3654–3669 (2022).

Robust Training with Data Augmentation for Medical Imaging Classification Medical Physics 49(6), 3654–3669 (2022)

Reference 2

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Observation e386807c-a9ae-4622-bd24-be904b1ce34f · outbound

This paper cites Applied Sciences 11(2), 672 (2021).

Robust Training with Data Augmentation for Medical Imaging Classification Applied Sciences 11(2), 672 (2021)

Reference 3

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This paper cites Monthly weather review 78(1), 1–3 (1950).

Robust Training with Data Augmentation for Medical Imaging Classification Monthly weather review 78(1), 1–3 (1950)

Reference 4

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Observation 0f01ad13-c321-47f1-938c-d29c3312415a · outbound

This paper cites COVID-19 Image Data Collection: Prospective Predictions Are the Future.

Robust Training with Data Augmentation for Medical Imaging Classification COVID-19 Image Data Collection: Prospective Predictions Are the Future

Reference 5

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Observation e37214fd-d70f-4565-81be-ae767b86f0b1 · outbound

This paper cites Artificial Intelligence in Medicine 132, 102386 (2022).

Robust Training with Data Augmentation for Medical Imaging Classification Artificial Intelligence in Medicine 132, 102386 (2022)

Reference 6

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Observation a40d33c8-cdd6-4d32-8fd9-ac532c641c4b · outbound

This paper cites Explaining and Harnessing Adversarial Examples.

Robust Training with Data Augmentation for Medical Imaging Classification Explaining and Harnessing Adversarial Examples

Reference 7

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Observation b7ffc807-e8bc-43b5-8e1a-92c5e6a5e792 · outbound

This paper cites In: 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp.

Robust Training with Data Augmentation for Medical Imaging Classification In: 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp

Reference 8

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Observation 242fed94-2f5f-4825-b9ec-aa11594c8f94 · outbound

This paper cites Benchmarking Neural Network Robustness to Common Corruptions and Perturbations.

Robust Training with Data Augmentation for Medical Imaging Classification Benchmarking Neural Network Robustness to Common Corruptions and Perturbations

Reference 9

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Observation 8afb8819-83e7-42de-9b6c-e284533f86bd · outbound

This paper cites AugMix: A Simple Data Processing Method to Improve Robustness and Uncertainty.

Robust Training with Data Augmentation for Medical Imaging Classification AugMix: A Simple Data Processing Method to Improve Robustness and Uncertainty

Reference 10

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Observation 53242403-ccc4-4e2c-ae31-6932dfde80a1 · outbound

This paper cites CVPR (2022).

Robust Training with Data Augmentation for Medical Imaging Classification CVPR (2022)

Reference 11

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Observation c9b8491e-5a28-4e1c-bdc3-e41b1dd1a6c7 · outbound

This paper cites JCO Clinical Cancer Informatics 6, e2100170 (2022).

Robust Training with Data Augmentation for Medical Imaging Classification JCO Clinical Cancer Informatics 6, e2100170 (2022)

Reference 12

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Observation f38c2b56-9c20-441d-8e41-2fc0b459982d · outbound

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Robust Training with Data Augmentation for Medical Imaging Classification Unresolved cited work

Reference 13

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Observation 74eed20b-bd52-44b1-a746-7a7c6e7b3fb7 · outbound

This paper cites Heliyon p.

Robust Training with Data Augmentation for Medical Imaging Classification Heliyon p

Reference 14

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Observation 04157473-63a1-4b95-912d-5f9a17e2613e · outbound

This paper cites Korean journal of radiology 20(3), 405–410 (2019).

Robust Training with Data Augmentation for Medical Imaging Classification Korean journal of radiology 20(3), 405–410 (2019)

Reference 15

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Observation 9c734ec9-3e2e-4984-bef2-21b3d464b880 · outbound

This paper cites FUTURE-AI: Guiding Principles and Consensus Recommendations for Trustworthy Artificial Intelligence in Medical Imaging.

Robust Training with Data Augmentation for Medical Imaging Classification FUTURE-AI: Guiding Principles and Consensus Recommendations for Trustworthy Artificial Intelligence in Medical Imaging

Reference 16

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Observation adc1deab-37f6-408b-85b2-3f6ea27b2041 · outbound

This paper cites In: 2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI), pp.

Robust Training with Data Augmentation for Medical Imaging Classification In: 2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI), pp

Reference 17

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Observation adde617d-2b3f-4632-b98f-2f19bd4371f3 · outbound

This paper cites Domain Generalization for Mammographic Image Analysis with Contrastive Learning.

Robust Training with Data Augmentation for Medical Imaging Classification Domain Generalization for Mammographic Image Analysis with Contrastive Learning

Reference 18

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Observation 2425e733-1e50-4336-a8a8-f900d1090904 · outbound

This paper cites Pattern Recognition 110, 107332 (2021).

Robust Training with Data Augmentation for Medical Imaging Classification Pattern Recognition 110, 107332 (2021)

Reference 19

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Observation 7c51fdc2-b549-416a-95e0-2c97a30d9ce6 · outbound

This paper cites Towards Deep Learning Models Resistant to Adversarial Attacks.

Robust Training with Data Augmentation for Medical Imaging Classification Towards Deep Learning Models Resistant to Adversarial Attacks

Reference 20

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Observation ff0d2799-4ff3-4fee-a98b-fcc45b05af3f · outbound

This paper cites In: NeurIPS ML Safety Workshop (2022).

Robust Training with Data Augmentation for Medical Imaging Classification In: NeurIPS ML Safety Workshop (2022)

Reference 21

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Observation abb45084-ecb0-4803-8d46-09925fda5e83 · outbound

This paper cites Proceedings of the AAAI Conference on Arti- ficial Intelligence 38(21), 23579–23581 (2024).

Robust Training with Data Augmentation for Medical Imaging Classification Proceedings of the AAAI Conference on Arti- ficial Intelligence 38(21), 23579–23581 (2024)

Reference 22

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Observation 1de6a5e4-8693-4062-8693-6010a203915f · outbound

This paper cites In: 2023 IEEE Conference on Artificial Intelligence (CAI), pp.

Robust Training with Data Augmentation for Medical Imaging Classification In: 2023 IEEE Conference on Artificial Intelligence (CAI), pp

Reference 23

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Observation 78a1d603-13eb-4398-ae34-5cb563bccbe9 · outbound

This paper cites In: 2023 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), pp.

Robust Training with Data Augmentation for Medical Imaging Classification In: 2023 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), pp

Reference 24

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This paper cites An overview of gradient descent optimization algorithms.

Robust Training with Data Augmentation for Medical Imaging Classification An overview of gradient descent optimization algorithms

Reference 25

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This paper cites Tools and Practices for Responsible AI Engineering.

Robust Training with Data Augmentation for Medical Imaging Classification Tools and Practices for Responsible AI Engineering

Reference 26

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Observation 5d59e089-408c-4ebf-99e7-9ff40ef73f99 · outbound

This paper cites IEEE transactions on neural networks 10(5), 988–999 (1999).

Robust Training with Data Augmentation for Medical Imaging Classification IEEE transactions on neural networks 10(5), 988–999 (1999)

Reference 27

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Robust Training with Data Augmentation for Medical Imaging Classification mixup: Beyond Empirical Risk Minimization

Reference 28

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This paper cites In: International Conference on Machine Learning (2019).

Robust Training with Data Augmentation for Medical Imaging Classification In: International Conference on Machine Learning (2019)

Reference 29

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