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Paper Citation Record · LEDGER

Comparative assessment of fairness definitions and bias mitigation strategies in machine learning-based diagnosis of Alzheimer's disease from MR images

As of 8 August 2026, this Paper Citation Record lists 28 of 28 outbound references and 0 inbound Pith citation observations for arXiv:2505.23528.

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

pith.paper-citation-record.v1
2505.23528 v1

Coverage vector

measured 28 of 28 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:47:36.810705Z

measured 28 of 28 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+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

28 of 28 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 7f434b90-8407-4f6c-8882-0710c897d0db · outbound

This paper cites Diversity and disparity in dementia: the impact of ethnoracial differences in alzheimer disease,.

Comparative assessment of fairness definitions and bias mitigation strategies in machine learning-based diagnosis of Alzheimer's disease from MR images Diversity and disparity in dementia: the impact of ethnoracial differences in alzheimer disease,

Reference 1

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Observation 49114a85-edd6-4890-994b-7997a8cfa35e · outbound

This paper cites Unraveling gender fairness analysis in deep learning prediction of alzheimer’s disease,.

Comparative assessment of fairness definitions and bias mitigation strategies in machine learning-based diagnosis of Alzheimer's disease from MR images Unraveling gender fairness analysis in deep learning prediction of alzheimer’s disease,

Reference 2

Resolution
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Observation bd2c4ced-d2aa-4f92-8cd0-d5586948c65c · outbound

This paper cites Machine learning in neuroimaging: Progress and challenges,.

Comparative assessment of fairness definitions and bias mitigation strategies in machine learning-based diagnosis of Alzheimer's disease from MR images Machine learning in neuroimaging: Progress and challenges,

Reference 3

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Observation ef95ad8c-c2b2-4641-bfc1-2e37f4e7449a · outbound

This paper cites Adapting machine learning diagnostic models to new populations using a small amount of data: Results from clinical neuroscience,.

Comparative assessment of fairness definitions and bias mitigation strategies in machine learning-based diagnosis of Alzheimer's disease from MR images Adapting machine learning diagnostic models to new populations using a small amount of data: Results from clinical neuroscience,

Reference 4

Resolution
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Observation c8a8d679-5e21-473b-b3f6-00d0705fb37b · outbound

This paper cites Addressing fairness issues in deep learning-based medical image analysis: a systematic review,.

Comparative assessment of fairness definitions and bias mitigation strategies in machine learning-based diagnosis of Alzheimer's disease from MR images Addressing fairness issues in deep learning-based medical image analysis: a systematic review,

Reference 5

Resolution
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This paper cites Sex and gender considerations in dementia: a call for global research,.

Comparative assessment of fairness definitions and bias mitigation strategies in machine learning-based diagnosis of Alzheimer's disease from MR images Sex and gender considerations in dementia: a call for global research,

Reference 6

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Observation 48c94a24-2fea-4b00-b97a-ea34497e141f · outbound

This paper cites MEDFAIR: Benchmarking Fairness for Medical Imaging.

Comparative assessment of fairness definitions and bias mitigation strategies in machine learning-based diagnosis of Alzheimer's disease from MR images MEDFAIR: Benchmarking Fairness for Medical Imaging

Reference 7

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Source-reported events for the cited work

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Observation 891a5962-7221-4e16-8853-8158968564a8 · outbound

This paper cites What’s fair about individual fairness?,.

Comparative assessment of fairness definitions and bias mitigation strategies in machine learning-based diagnosis of Alzheimer's disease from MR images What’s fair about individual fairness?,

Reference 8

Resolution
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Observation 68d8238f-534b-490d-8744-c13b8048ea4b · outbound

This paper cites Counterfactual fairness,.

Comparative assessment of fairness definitions and bias mitigation strategies in machine learning-based diagnosis of Alzheimer's disease from MR images Counterfactual fairness,

Reference 9

Resolution
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Observation ab5800cd-e185-49db-9b24-44cb6a3c8509 · outbound

This paper cites Using explainability for bias mitigation: A case study for fair recruitment assessment,.

Comparative assessment of fairness definitions and bias mitigation strategies in machine learning-based diagnosis of Alzheimer's disease from MR images Using explainability for bias mitigation: A case study for fair recruitment assessment,

Reference 10

Resolution
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Observation 2987b2d2-25b5-4493-b2b3-f3fcfb8fd88f · outbound

This paper cites Fair machine learning in healthcare: A survey,.

Comparative assessment of fairness definitions and bias mitigation strategies in machine learning-based diagnosis of Alzheimer's disease from MR images Fair machine learning in healthcare: A survey,

Reference 11

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Observation 6c88485c-d426-4471-8307-8eddfbee4a58 · outbound

This paper cites Algorithmic fairness of machine learning models for alzheimer disease progression,.

Comparative assessment of fairness definitions and bias mitigation strategies in machine learning-based diagnosis of Alzheimer's disease from MR images Algorithmic fairness of machine learning models for alzheimer disease progression,

Reference 12

Resolution
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This paper cites Feature robustness and sex differences in medical imaging: a case study in mri-based alzheimer’s disease detection,.

Comparative assessment of fairness definitions and bias mitigation strategies in machine learning-based diagnosis of Alzheimer's disease from MR images Feature robustness and sex differences in medical imaging: a case study in mri-based alzheimer’s disease detection,

Reference 13

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Observation 2de7aa2f-f5e5-426a-87d2-2bcb73674cd1 · outbound

This paper cites Auditing unfair biases in cnn-based diagnosis of alzheimer’s disease,.

Comparative assessment of fairness definitions and bias mitigation strategies in machine learning-based diagnosis of Alzheimer's disease from MR images Auditing unfair biases in cnn-based diagnosis of alzheimer’s disease,

Reference 14

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Source-reported events for the cited work

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Observation e13d0968-1501-4366-914a-b267da6ed89b · outbound

This paper cites Is there a trade-off between fairness and accuracy? a perspective using mismatched hypothesis testing,.

Comparative assessment of fairness definitions and bias mitigation strategies in machine learning-based diagnosis of Alzheimer's disease from MR images Is there a trade-off between fairness and accuracy? a perspective using mismatched hypothesis testing,

Reference 15

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Source-reported events for the cited work

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Observation e65b212c-932c-47d2-9ac7-31eedf193557 · outbound

This paper cites Accurate fairness: Improving individual fairness without trading accuracy,.

Comparative assessment of fairness definitions and bias mitigation strategies in machine learning-based diagnosis of Alzheimer's disease from MR images Accurate fairness: Improving individual fairness without trading accuracy,

Reference 16

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Observation aa8af04b-8e50-48b8-b2e0-01bc92b46335 · outbound

This paper cites Optimizing fairness and accuracy: a pareto optimal approach for decision-making,.

Comparative assessment of fairness definitions and bias mitigation strategies in machine learning-based diagnosis of Alzheimer's disease from MR images Optimizing fairness and accuracy: a pareto optimal approach for decision-making,

Reference 17

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Observation bfaa0316-4002-480c-bff2-07bdadd63e39 · outbound

This paper cites Habes, R.

Comparative assessment of fairness definitions and bias mitigation strategies in machine learning-based diagnosis of Alzheimer's disease from MR images Habes, R

Reference 18

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This paper cites Muse: Multi-atlas region segmentation utilizing ensembles of registration algo- rithms and parameters, and locally optimal atlas selection,.

Comparative assessment of fairness definitions and bias mitigation strategies in machine learning-based diagnosis of Alzheimer's disease from MR images Muse: Multi-atlas region segmentation utilizing ensembles of registration algo- rithms and parameters, and locally optimal atlas selection,

Reference 19

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Observation 626261a9-a682-447c-ab15-d052c47b8a3b · outbound

This paper cites Harmonization of large multi-site imaging datasets: Application to 10,232 mris for the analysis of imaging patterns of structural brain change throughout the lifespan,.

Comparative assessment of fairness definitions and bias mitigation strategies in machine learning-based diagnosis of Alzheimer's disease from MR images Harmonization of large multi-site imaging datasets: Application to 10,232 mris for the analysis of imaging patterns of structural brain change throughout the lifespan,

Reference 20

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This paper cites A comprehensive interpretable machine learning framework for mild cognitive impairment and alzheimer’s disease diagnosis,.

Comparative assessment of fairness definitions and bias mitigation strategies in machine learning-based diagnosis of Alzheimer's disease from MR images A comprehensive interpretable machine learning framework for mild cognitive impairment and alzheimer’s disease diagnosis,

Reference 21

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This paper cites Mitigating unwanted biases with adversarial learning,.

Comparative assessment of fairness definitions and bias mitigation strategies in machine learning-based diagnosis of Alzheimer's disease from MR images Mitigating unwanted biases with adversarial learning,

Reference 22

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This paper cites Ai fairness 360: An extensible toolkit for detecting and mitigating algorithmic bias,.

Comparative assessment of fairness definitions and bias mitigation strategies in machine learning-based diagnosis of Alzheimer's disease from MR images Ai fairness 360: An extensible toolkit for detecting and mitigating algorithmic bias,

Reference 23

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This paper cites Decision theory for discrimination-aware classification,.

Comparative assessment of fairness definitions and bias mitigation strategies in machine learning-based diagnosis of Alzheimer's disease from MR images Decision theory for discrimination-aware classification,

Reference 24

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This paper cites Structural mri predictors of late-life cognition differ across african americans, hispanics, and whites,.

Comparative assessment of fairness definitions and bias mitigation strategies in machine learning-based diagnosis of Alzheimer's disease from MR images Structural mri predictors of late-life cognition differ across african americans, hispanics, and whites,

Reference 25

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This paper cites Sex and gender differences in cognitive and brain reserve: Implications for alzheimer’s disease in women,.

Comparative assessment of fairness definitions and bias mitigation strategies in machine learning-based diagnosis of Alzheimer's disease from MR images Sex and gender differences in cognitive and brain reserve: Implications for alzheimer’s disease in women,

Reference 26

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This paper cites Sex differences in brain mri using deep learning toward fairer healthcare outcomes,.

Comparative assessment of fairness definitions and bias mitigation strategies in machine learning-based diagnosis of Alzheimer's disease from MR images Sex differences in brain mri using deep learning toward fairer healthcare outcomes,

Reference 27

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This paper cites Counterfactual fairness is basically demographic parity,.

Comparative assessment of fairness definitions and bias mitigation strategies in machine learning-based diagnosis of Alzheimer's disease from MR images Counterfactual fairness is basically demographic parity,

Reference 28

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Pith citing papers

No inbound Pith citation observations are available.