TransFair: Transferring Fairness from Ocular Disease Classification to Progression Prediction | Paper Citation Record

Observation 2168f340-be9a-4d8c-bc8a-6962d0d68bb2 · outbound

This paper cites Multimodal biomedical ai,.

TransFair: Transferring Fairness from Ocular Disease Classification to Progression Prediction Multimodal biomedical ai,

Reference 1

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Observation 94254943-6ea9-4ae8-bf76-3b23858295fd · outbound

This paper cites On the challenges and perspectives of foundation models for medical image analysis,.

TransFair: Transferring Fairness from Ocular Disease Classification to Progression Prediction On the challenges and perspectives of foundation models for medical image analysis,

Reference 2

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This paper cites The current status and future of fda-approved artificial intelligence tools in chest radiology in the united states,.

TransFair: Transferring Fairness from Ocular Disease Classification to Progression Prediction The current status and future of fda-approved artificial intelligence tools in chest radiology in the united states,

Reference 3

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Observation 5d0a53d1-0837-44e4-af91-62293a52b50b · outbound

This paper cites Fda-cleared artificial intelligence and machine learning-based medical devices and their 510 (k) predicate networks,.

TransFair: Transferring Fairness from Ocular Disease Classification to Progression Prediction Fda-cleared artificial intelligence and machine learning-based medical devices and their 510 (k) predicate networks,

Reference 4

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This paper cites Artificial intelligence in disease diagnosis: a systematic literature review, synthesizing frame- work and future research agenda,.

TransFair: Transferring Fairness from Ocular Disease Classification to Progression Prediction Artificial intelligence in disease diagnosis: a systematic literature review, synthesizing frame- work and future research agenda,

Reference 5

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Observation bc93e87f-e0eb-44af-b753-be5685a552e1 · outbound

This paper cites Expert-level detection of pathologies from unannotated chest x-ray images via self-supervised learning,.

TransFair: Transferring Fairness from Ocular Disease Classification to Progression Prediction Expert-level detection of pathologies from unannotated chest x-ray images via self-supervised learning,

Reference 6

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Observation a7cd4d94-52f2-4b70-9f58-d62bda8c510d · outbound

This paper cites Applications of deep learning in fundus images: A review,.

TransFair: Transferring Fairness from Ocular Disease Classification to Progression Prediction Applications of deep learning in fundus images: A review,

Reference 7

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Observation 2fe580e8-093c-44b1-8f84-52ce91e73c75 · outbound

This paper cites Rnflt2vec: Artifact- corrected representation learning for retinal nerve fiber layer thickness maps,.

TransFair: Transferring Fairness from Ocular Disease Classification to Progression Prediction Rnflt2vec: Artifact- corrected representation learning for retinal nerve fiber layer thickness maps,

Reference 8

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Observation 5cdbd068-03fd-462e-896f-77ab3209009f · outbound

This paper cites Global prevalence of glaucoma and projections of glaucoma burden through 2040: a systematic review and meta-analysis,.

TransFair: Transferring Fairness from Ocular Disease Classification to Progression Prediction Global prevalence of glaucoma and projections of glaucoma burden through 2040: a systematic review and meta-analysis,

Reference 9

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Observation e793b9c9-c46d-4bf7-a588-63b9e02a0b38 · outbound

This paper cites Generating synthetic mixed-type longitudinal electronic health records for artificial intelligent applica- tions,.

TransFair: Transferring Fairness from Ocular Disease Classification to Progression Prediction Generating synthetic mixed-type longitudinal electronic health records for artificial intelligent applica- tions,

Reference 10

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Observation 11871528-b640-48be-b3c9-8774468a2320 · outbound

This paper cites Imageflownet: fore- casting multiscale image-level trajectories of disease progression with irregularlysampled longitudinal medical images,.

TransFair: Transferring Fairness from Ocular Disease Classification to Progression Prediction Imageflownet: fore- casting multiscale image-level trajectories of disease progression with irregularlysampled longitudinal medical images,

Reference 11

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Observation 807730e3-fea0-4281-8e6d-6a051f75bfc6 · outbound

This paper cites Algorithmic fairness in artificial intel- ligence for medicine and healthcare,.

TransFair: Transferring Fairness from Ocular Disease Classification to Progression Prediction Algorithmic fairness in artificial intel- ligence for medicine and healthcare,

Reference 12

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Observation 282b5ac6-97f4-4418-90d4-96ebdaebf650 · outbound

This paper cites Harvard glaucoma fairness: a retinal nerve disease dataset for fairness learning and fair identity normalization,.

TransFair: Transferring Fairness from Ocular Disease Classification to Progression Prediction Harvard glaucoma fairness: a retinal nerve disease dataset for fairness learning and fair identity normalization,

Reference 13

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Observation 23838a7a-9b17-436c-9b1d-530a43c9be52 · outbound

This paper cites Fairseg: A large-scale medical image segmentation dataset for fairness learning using segment anything model with fair error-bound scaling,.

TransFair: Transferring Fairness from Ocular Disease Classification to Progression Prediction Fairseg: A large-scale medical image segmentation dataset for fairness learning using segment anything model with fair error-bound scaling,

Reference 14

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This paper cites An algorithmic approach to reducing unexplained pain dispar- ities in underserved populations,.

TransFair: Transferring Fairness from Ocular Disease Classification to Progression Prediction An algorithmic approach to reducing unexplained pain dispar- ities in underserved populations,

Reference 15

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Observation 2a731036-c632-47bd-af03-8f814e870fef · outbound

This paper cites Algorithmic encoding of protected characteristics in chest x-ray disease detection models,.

TransFair: Transferring Fairness from Ocular Disease Classification to Progression Prediction Algorithmic encoding of protected characteristics in chest x-ray disease detection models,

Reference 16

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Observation 55fdd4b9-875d-4a1d-8947-e19b2d4c0443 · outbound

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

TransFair: Transferring Fairness from Ocular Disease Classification to Progression Prediction Algorithmic fairness of machine learning models for alzheimer disease progression,

Reference 17

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Observation 42c21f63-6de8-4d4f-b8eb-4089159ca94e · outbound

This paper cites Fairness in deep learning: A survey on vision and language research,.

TransFair: Transferring Fairness from Ocular Disease Classification to Progression Prediction Fairness in deep learning: A survey on vision and language research,

Reference 18

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Observation 9e9113b0-de25-406b-8c32-9888f396956a · outbound

This paper cites Equitable deep learning for diabetic retinopathy detection using multi-dimensional retinal imaging with fair adaptive scaling: a retrospective study,.

TransFair: Transferring Fairness from Ocular Disease Classification to Progression Prediction Equitable deep learning for diabetic retinopathy detection using multi-dimensional retinal imaging with fair adaptive scaling: a retrospective study,

Reference 19

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This paper cites Harvard eye fairness: A large-scale 3d imaging dataset for equitable eye diseases screening and fair identity scaling,.

TransFair: Transferring Fairness from Ocular Disease Classification to Progression Prediction Harvard eye fairness: A large-scale 3d imaging dataset for equitable eye diseases screening and fair identity scaling,

Reference 20

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Observation 4afde048-aad2-4bb5-8aff-5f9c47dadbb4 · outbound

This paper cites FairDomain: Achieving Fairness in Cross-Domain Medical Image Segmentation and Classification.

TransFair: Transferring Fairness from Ocular Disease Classification to Progression Prediction FairDomain: Achieving Fairness in Cross-Domain Medical Image Segmentation and Classification

Reference 21

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This paper cites Efficientnet: Rethinking model scaling for con- volutional neural networks,.

TransFair: Transferring Fairness from Ocular Disease Classification to Progression Prediction Efficientnet: Rethinking model scaling for con- volutional neural networks,

Reference 22

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This paper cites Machine learning techniques for ophthalmic data processing: a review,.

TransFair: Transferring Fairness from Ocular Disease Classification to Progression Prediction Machine learning techniques for ophthalmic data processing: a review,

Reference 23

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This paper cites Classification of retinal diseases based on oct images,.

TransFair: Transferring Fairness from Ocular Disease Classification to Progression Prediction Classification of retinal diseases based on oct images,

Reference 24

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This paper cites Application of deep learning for retinal image analysis: A review,.

TransFair: Transferring Fairness from Ocular Disease Classification to Progression Prediction Application of deep learning for retinal image analysis: A review,

Reference 25

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Observation 3282f078-c4b0-45d4-b792-dd63b5a82779 · outbound

This paper cites Ocular disease detection systems based on fundus images: a survey,.

TransFair: Transferring Fairness from Ocular Disease Classification to Progression Prediction Ocular disease detection systems based on fundus images: a survey,

Reference 26

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Observation 4f99a75a-72c1-4d2e-8edd-4d00224fd4e2 · outbound

This paper cites A large-scale database and a cnn model for attention-based glaucoma detection,.

TransFair: Transferring Fairness from Ocular Disease Classification to Progression Prediction A large-scale database and a cnn model for attention-based glaucoma detection,

Reference 27

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This paper cites A generalizable deep learning regression model for automated glaucoma screening from fundus images,.

TransFair: Transferring Fairness from Ocular Disease Classification to Progression Prediction A generalizable deep learning regression model for automated glaucoma screening from fundus images,

Reference 28

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This paper cites Technical and imaging factors influencing performance of deep learning systems for diabetic retinopathy,.

TransFair: Transferring Fairness from Ocular Disease Classification to Progression Prediction Technical and imaging factors influencing performance of deep learning systems for diabetic retinopathy,

Reference 29

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This paper cites A review of deep learning for screening, diagnosis, and detection of glaucoma progression,.

TransFair: Transferring Fairness from Ocular Disease Classification to Progression Prediction A review of deep learning for screening, diagnosis, and detection of glaucoma progression,

Reference 30

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This paper cites Predicting glaucoma development with longitudinal deep learning predictions from fundus photographs,.

TransFair: Transferring Fairness from Ocular Disease Classification to Progression Prediction Predicting glaucoma development with longitudinal deep learning predictions from fundus photographs,

Reference 31

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This paper cites Deep learning algorithm predicts diabetic retinopathy progression in individual patients,.

TransFair: Transferring Fairness from Ocular Disease Classification to Progression Prediction Deep learning algorithm predicts diabetic retinopathy progression in individual patients,

Reference 32

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This paper cites Toward fairness in artificial intelligence for medical image analysis: identifi- cation and mitigation of potential biases in the roadmap from data collection to model deployment,.

TransFair: Transferring Fairness from Ocular Disease Classification to Progression Prediction Toward fairness in artificial intelligence for medical image analysis: identifi- cation and mitigation of potential biases in the roadmap from data collection to model deployment,

Reference 33

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This paper cites Addressing fairness in artificial intelligence for medical imaging,.

TransFair: Transferring Fairness from Ocular Disease Classification to Progression Prediction Addressing fairness in artificial intelligence for medical imaging,

Reference 34

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TransFair: Transferring Fairness from Ocular Disease Classification to Progression Prediction Bias mimicking: A simple sampling approach for bias mitigation,

Reference 35

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This paper cites Ai recognition of patient race in medical imaging: a modelling study,.

TransFair: Transferring Fairness from Ocular Disease Classification to Progression Prediction Ai recognition of patient race in medical imaging: a modelling study,

Reference 36

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This paper cites An adversarial training framework for mitigating algorithmic biases in clinical machine learning,.

TransFair: Transferring Fairness from Ocular Disease Classification to Progression Prediction An adversarial training framework for mitigating algorithmic biases in clinical machine learning,

Reference 37

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TransFair: Transferring Fairness from Ocular Disease Classification to Progression Prediction A Unified Post-Processing Framework for Group Fairness in Classification

Reference 38

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TransFair: Transferring Fairness from Ocular Disease Classification to Progression Prediction Post-processing fairness with minimal changes

Reference 39

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This paper cites Generative models improve fairness of medical classifiers under distribution shifts,.

TransFair: Transferring Fairness from Ocular Disease Classification to Progression Prediction Generative models improve fairness of medical classifiers under distribution shifts,

Reference 40

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This paper cites Knowledge distillation in medical data mining: a survey,.

TransFair: Transferring Fairness from Ocular Disease Classification to Progression Prediction Knowledge distillation in medical data mining: a survey,

Reference 41

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This paper cites Adaptive knowledge distillation for high-quality un- supervised mri reconstruction with model-driven priors,.

TransFair: Transferring Fairness from Ocular Disease Classification to Progression Prediction Adaptive knowledge distillation for high-quality un- supervised mri reconstruction with model-driven priors,

Reference 42

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This paper cites Categorical relation-preserving contrastive knowledge distillation for medical image classification,.

TransFair: Transferring Fairness from Ocular Disease Classification to Progression Prediction Categorical relation-preserving contrastive knowledge distillation for medical image classification,

Reference 43

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This paper cites Kullback-leibler divergence,.

TransFair: Transferring Fairness from Ocular Disease Classification to Progression Prediction Kullback-leibler divergence,

Reference 44

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This paper cites Comparison of different methods for detecting glaucomatous visual field progression,.

TransFair: Transferring Fairness from Ocular Disease Classification to Progression Prediction Comparison of different methods for detecting glaucomatous visual field progression,

Reference 45

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

TransFair: Transferring Fairness from Ocular Disease Classification to Progression Prediction Very Deep Convolutional Networks for Large-Scale Image Recognition

Reference 46

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TransFair: Transferring Fairness from Ocular Disease Classification to Progression Prediction Densely connected convolutional networks,

Reference 47

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This paper cites Deep residual learning for image recognition,.

TransFair: Transferring Fairness from Ocular Disease Classification to Progression Prediction Deep residual learning for image recognition,

Reference 48

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This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

TransFair: Transferring Fairness from Ocular Disease Classification to Progression Prediction An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 49

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This paper cites Data Decisions and Theoretical Implications when Adversarially Learning Fair Representations.

TransFair: Transferring Fairness from Ocular Disease Classification to Progression Prediction Data Decisions and Theoretical Implications when Adversarially Learning Fair Representations

Reference 50

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This paper cites Masked au- toencoders are scalable vision learners,.

TransFair: Transferring Fairness from Ocular Disease Classification to Progression Prediction Masked au- toencoders are scalable vision learners,

Reference 51

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Observation 5735fc12-239a-43fe-a5f1-6086f7fda958 · outbound

This paper cites Decoupled weight decay regularization,.

TransFair: Transferring Fairness from Ocular Disease Classification to Progression Prediction Decoupled weight decay regularization,

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