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In the current development and deployment of many artificial intelligence (AI) systems in healthcare, algorithm fairness is a challenging problem in delivering equitable care.
Classification of hospital patients as” surgical”: implications of the shift to icd-9-cm
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Smoking vs other risk factors as the cause of smoking-attributable deaths: confounding in the courtroom
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Social networks of drug users in high-risk sites: Finding the connections
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Smote: synthetic minority over-sampling technique
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Clinical uncertainty and healthcare disparities
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Medicine and the racial divide
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Data security and protection in cross-institutional electronic patient records
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Compiling the evidence: The national healthcare disparities reports
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Social determinants of health inequalities
Marmot, M · 2005
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Cardiovascular risk factor profiles and kidney function stage in the us general population: the nhanes iii study
Foley, R. N., Wang, C. & Collins, A. J · 2005
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Performance of the modification of diet in renal disease and cockcroft-gault equations in the estimation of gfr in health and in chronic kidney disease
Poggio ED, G. T. V. L. F. H. P., Wang X · 2005
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Geography is a better determinant of human genetic differentiation than ethnicity
Manica, A., Prugnolle, F. & Balloux, F · 2005
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Maternal mortality: who, when, where, and why
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The osteoarthritis initiative
Nevitt, M., Felson, D. & Lester, G · 2006
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Using standardized serum creatinine values in the modification of diet in renal disease study equation for estimating glomerular filtration rate
Levey AS, G. T. S. L. Z. Y. H. S. K. J. V. L. F., Coresh J · 2006
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Nightmare at test time: robust learning by feature deletion
Globerson, A. & Roweis, S · 2006
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Optimal design of experiments (SIAM, 2006)
Pukelsheim, F · 2006
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Covariate shift adaptation by importance weighted cross validation
Sugiyama, M., Krauledat, M. & Müller, K.-R · 2007
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Bone age assessment of children using a digital hand atlas
Gertych, A., Zhang, A., Sayre, J., Pospiech-Kurkowska, S. & Huang, H · 2007
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Building classifiers with independency constraints
Calders, T., Kamiran, F. & Pechenizkiy, M · 2009
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Dataset shift in machine learning (Mit Press, 2009)
Quiñonero-Candela, J., Sugiyama, M., Lawrence, N. D. & Schwaighofer, A · 2009
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Estimation of the warfarin dose with clinical and pharmacogenetic data · 2009
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Population-based fracture risk assessment and osteoporosis treatment disparities by race and gender
Curtis, J. R. et al · 2009
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Sampling: design and analysis: Nelson education (2009)
Lohr, S. L · 2009
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Food insecurity is associated with chronic disease among low-income nhanes participants
Seligman, H. K., Laraia, B. A. & Kushel, M. B · 2010
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Current status of estimated glomerular filtration rate (egfr) equations for asians and an approach to create a common egfr equation
Matsuo, S., Yasuda, Y., IMAi, E. & Horio, M · 2010
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Learning bounds for importance weighting
Cortes, C., Mansour, Y. & Mohri, M · 2010
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The emerge network: a consortium of biorepositories linked to electronic medical records data for conducting genomic studies
McCarty, C. A. et al · 2011
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The national lung screening trial: overview and study design
Team, N. L. S. T. R · 2011
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Disparities in breast cancer characteristics and outcomes by race/ethnicity
Ooi, S. L., Martinez, M. E. & Li, C. I · 2011
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Fairness-aware learning through regularization approach
Kamishima, T., Akaho, S. & Sakuma, J · 2011
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Data preprocessing techniques for classification without discrimination
Kamiran, F. & Calders, T · 2012
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The age-related eye disease study 2 (areds2): study design and baseline characteristics (areds2 report number 1)
Chew, E. Y. et al · 2012
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De-identification methods for open health data: the case of the heritage health prize claims dataset
El Emam, K. et al · 2012
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The influence of race and ethnicity on the biology of cancer
Henderson, B. E., Lee, N. H., Seewaldt, V. & Shen, H · 2012
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Strategies for de-identification and anonymization of electronic health record data for use in multicenter research studies
Kushida, C. A. et al · 2012
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Fairness-aware classifier with prejudice remover regularizer
Kamishima, T., Akaho, S., Asoh, H. & Sakuma, J · 2012
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The applicability of egfr equations to different populations
Delanaye, P. & Mariat, C · 2013
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The electronic medical records and genomics (emerge) network: past, present, and future
Gottesman, O. et al · 2013
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Integrative analysis of complex cancer genomics and clinical profiles using the cbioportal
Gao, J. et al · 2013
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Learning fair representations
Zemel, R., Wu, Y., Swersky, K., Pitassi, T. & Dwork, C · 2013
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Deep inside convolutional networks: Visualising image classification models and saliency maps
Simonyan, K., Vedaldi, A. & Zisserman, A · 2013
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A prospective, molecular epidemiology study of egfr mutations in asian patients with advanced non–small-cell lung cancer of adenocarcinoma histology (pioneer)
Shi, Y. et al · 2014
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Is racism a fundamental cause of inequalities in health?
Phelan, J. C. & Link, B. G · 2015
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Access disparity and health inequality of the elderly: unmet needs and delayed healthcare
Yamada, T. et al · 2015
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Unsupervised domain adaptation by backpropagation
Ganin, Y. & Lempitsky, V · 2015
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Memorial sloan kettering-integrated mutation profiling of actionable cancer targets (msk-impact): a hybridization capture-based next-generation sequencing clinical assay for solid tumor molecular oncology
Cheng, D. T. et al · 2015
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Uk biobank: an open access resource for identifying the causes of a wide range of complex diseases of middle and old age
Sudlow, C. et al · 2015
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The cptac data portal: a resource for cancer proteomics research
Edwards, N. J. et al · 2015
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Effect of genetic african ancestry on egfr and kidney disease
Udler, M. S. et al · 2015
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Diagnosis and surgical delays in african american and white women with early-stage breast cancer
George, P. et al · 2015
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Dalsa: domain adaptation for supervised learning from sparsely annotated mr images
Goetz, M. et al · 2015
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Addressing social determinants of health and health inequalities
Adler, N. E., Glymour, M. M. & Fielding, J · 2016
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A computer program used for bail and sentencing decisions was labeled biased against blacks. it’s actually not that clear
Feller, A., Pierson, E., Corbett-Davies, S. & Goel, S · 2016
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Equality of opportunity in supervised learning
Hardt, M., Price, E. & Srebro, N · 2016
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Mimic-iii, a freely accessible critical care database
Johnson, A. E. et al · 2016
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Racial/ethnic disparities in genomic sequencing
Spratt, D. E. et al · 2016
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Genetic misdiagnoses and the potential for health disparities
Manrai, A. K. et al · 2016
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Federated learning: Strategies for improving communication efficiency
Konečnỳ, J. et al · 2016
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beta-vae: Learning basic visual concepts with a constrained variational framework (2016)
Higgins, I. et al · 2016
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Unsupervised domain adaptation techniques based on auto-encoder for non-stationary eeg-based emotion recognition
Chai, X. et al · 2016
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Domain adaptation for alzheimer’s disease diagnostics
Wachinger, C., Reuter, M., Initiative, A. D. N. et al · 2016
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Big data’s disparate impact
Barocas, S. & Selbst, A. D · 2016
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Weapons of math destruction: How big data increases inequality and threatens democracy (Crown, 2016)
O’neil, C · 2016
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Celis, L. E., Deshpande, A., Kathuria, T. & Vishnoi, N. K · 2016
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Lgbt healthcare disparities: What progress have we made?
Bonvicini, K. A · 2017
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Trends in maternal mortality by socio-demographic characteristics and cause of death in 27 states and the district of columbia
MacDorman, M. F., Declercq, E. & Thoma, M. E · 2017
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Inherent Trade-Offs in the Fair Determination of Risk Scores
Kleinberg, J., Mullainathan, S. & Raghavan, M · 2017
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Trends in opioid-related inpatient stays shifted after the us transitioned to icd-10-cm diagnosis coding in 2015
Heslin, K. C. et al · 2017
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The variational fair autoencoder (2017)
Louizos, C., Swersky, K., Li, Y., Welling, M. & Zemel, R · 2017
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Genomics, health disparities, and missed opportunities for the nation’s research agenda
West, K. M., Blacksher, E. & Burke, W · 2017
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Diagnostic assessment of deep learning algorithms for detection of lymph node metastases in women with breast cancer
Bejnordi, B. E. et al · 2017
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Racial disparities in patient survival and tumor mutation burden, and the association between tumor mutation burden and cancer incidence rate
Zhang, W., Edwards, A., Flemington, E. K. & Zhang, K · 2017
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Practical secure aggregation for privacy-preserving machine learning
Bonawitz, K. et al · 2017
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Fairer machine learning in the real world: Mitigating discrimination without collecting sensitive data
Veale, M. & Binns, R · 2017
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Deep gradient compression: Reducing the communication bandwidth for distributed training
Lin, Y., Han, S., Mao, H., Wang, Y. & Dally, W. J · 2017
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Communication-efficient learning of deep networks from decentralized data
McMahan, B., Moore, E., Ramage, D., Hampson, S. & y Arcas, B. A · 2017
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Causal effect inference with deep latent-variable models
Louizos, C. et al · 2017
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Grad-cam: Visual explanations from deep networks via gradient-based localization
Selvaraju, R. R. et al · 2017
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Axiomatic attribution for deep networks
Sundararajan, M., Taly, A. & Yan, Q · 2017
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A unified approach to interpreting model predictions
Lundberg, S. M. & Lee, S.-I · 2017
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Fairness constraints: Mechanisms for fair classification
Zafar, M. B., Valera, I., Rogriguez, M. G. & Gummadi, K. P · 2017
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Pleiss, G., Raghavan, M., Wu, F., Kleinberg, J. & Weinberger, K. Q · 2017
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Fairness beyond disparate treatment & disparate impact: Learning classification without disparate mistreatment
Zafar, M. B., Valera, I., Gomez Rodriguez, M. & Gummadi, K. P · 2017
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Gender shades: Intersectional accuracy disparities in commercial gender classification
Buolamwini, J. & Gebru, T · 2018
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The accuracy, fairness, and limits of predicting recidivism
Dressel, J. & Farid, H · 2018
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The moral machine experiment
Awad, E. et al · 2018
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Implementing machine learning in health care—addressing ethical challenges
Char, D. S., Shah, N. H. & Magnus, D · 2018
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The measure and mismeasure of fairness: A critical review of fair machine learning
Corbett-Davies, S. & Goel, S · 2018
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Adaptive sensitive reweighting to mitigate bias in fairness-aware classification
Krasanakis, E., Spyromitros-Xioufis, E., Papadopoulos, S. & Kompatsiaris, Y · 2018
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Mitigating unwanted biases with adversarial learning
Zhang, B. H., Lemoine, B. & Mitchell, M · 2018
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Fairness through computationally-bounded awareness
Kim, M. P., Reingold, O. & Rothblum, G. N · 2018
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A systematic study of the class imbalance problem in convolutional neural networks
Buda, M., Maki, A. & Mazurowski, M. A · 2018
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An integrated tcga pan-cancer clinical data resource to drive high-quality survival outcome analytics
Liu, J. et al · 2018
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Racial disparities and mistrust in end-of-life care
Boag, W., Suresh, H., Celi, L. A., Szolovits, P. & Ghassemi, M · 2018
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The eicu collaborative research database, a freely available multi-center database for critical care research
Pollard, T. J. et al · 2018
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Predict responsibly: Improving fairness and accuracy by learning to defer
Madras, D., Pitassi, T. & Zemel, R · 2018
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Gradient reversal against discrimination (2018)
Raff, E. & Sylvester, J · 2018
Cited alongside, same era.
Learning adversarially fair and transferable representations
Madras, D., Creager, E., Pitassi, T. & Zemel, R · 2018
Cited alongside, same era.
Beyond consent: building trusting relationships with diverse populations in precision medicine research
Kraft, S. A. et al · 2018
Cited alongside, same era.
Lack of diversity in genomic databases is a barrier to translating precision medicine research into practice
Assessing algorithmic fairness with unobserved protected class using data combination
Kallus, N., Mao, X. & Zhou, A · 2020
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Causality matters in medical imaging
Castro, D. C., Walker, I. & Glocker, B · 2020
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Cancer health disparities in racial/ethnic minorities in the united states
Zavala, V. A. et al · 2020
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Pan-cancer image-based detection of clinically actionable genetic alterations
Kather, J. N. et al · 2020
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Pan-cancer computational histopathology reveals mutations, tumor composition and prognosis
Fu, Y. et al · 2020
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Racial disparities, frax, and the care of patients with osteoporosis
Lewiecki, W. N. . S. A., E · 2020
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Landry, L. G., Ali, N., Williams, D. R., Rehm, H. L. & Bonham, V. L · 2018
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Examining how race, ethnicity, and ancestry data are used in biomedical research
Bonham VL, P.-S. E., Green ED · 2018
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A brief history of frax
Kanis JA, H. N. M. E., Johansson H · 2018
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Prediction of cardiovascular risk factors from retinal fundus photographs via deep learning
Poplin, R. et al · 2018
Cited alongside, same era.
Federated learning of predictive models from federated electronic health records
Brisimi, T. S. et al · 2018
Cited alongside, same era.
Why is my classifier discriminatory?
Chen, I., Johansson, F. D. & Sontag, D · 2018
Cited alongside, same era.
Odal: A one-shot distributed algorithm to perform logistic regressions on electronic health records data from multiple clinical sites
Duan, R., Boland, M. R., Moore, J. H. & Chen, Y · 2018
Cited alongside, same era.
Later among the works it cites.
Deep fair clustering for visual learning
Li, P., Zhao, H. & Liu, H · 2020
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The clinician and dataset shift in artificial intelligence
Finlayson, S. G. et al · 2020
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Fairness warnings and fair-maml: learning fairly with minimal data
Slack, D., Friedler, S. A. & Givental, E · 2020
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Don’t ignore genetic data from minority populations (2020)
Sun, R. et al · 2020
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Federated transfer learning for eeg signal classification
Ju, C. et al · 2020
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The future of digital health with federated learning
Rieke, N. et al · 2020
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Federated learning in medicine: facilitating multi-institutional collaborations without sharing patient data
Sheller, M. J. et al · 2020
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Privacy-first health research with federated learning
Hernandez, J. B. et al · 2020
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Federated learning for computational pathology on gigapixel whole slide images
Lu, M. Y. et al · 2020
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The genomics research and innovation network: creating an interoperable, federated, genomics learning system
Mandl, K. D. et al · 2020
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Do we really need to access the source data? source hypothesis transfer for unsupervised domain adaptation
Liang, J., Hu, D. & Feng, J · 2020
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Privacy-preserving unsupervised domain adaptation in federated setting
Song, L., Ma, C., Zhang, G. & Zhang, Y · 2020
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Multi-site fmri analysis using privacy-preserving federated learning and domain adaptation: Abide results
Li, X. et al · 2020
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Mitigating bias in federated learning
Abay, A. et al · 2020
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Co-designing checklists to understand organizational challenges and opportunities around fairness in ai
Madaio, M. A., Stark, L., Wortman Vaughan, J. & Wallach, H · 2020
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Private fl-gan: Differential privacy synthetic data generation based on federated learning
Xin, B. et al · 2020
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When causal inference meets deep learning
Luo, Y., Peng, J. & Ma, J · 2020
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Fairness for robust log loss classification
Rezaei, A., Fathony, R., Memarrast, O. & Ziebart, B · 2020
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Fair: Fair adversarial instance re-weighting
Petrović, A., Nikolić, M., Radovanović, S., Delibašić, B. & Jovanović, M · 2020
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A simple framework for contrastive learning of visual representations
Chen, T., Kornblith, S., Norouzi, M. & Hinton, G · 2020
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Assessing the validity of saliency maps for abnormality localization in medical imaging
Arun, N. T. et al · 2020
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Interpreting interpretability: understanding data scientists’ use of interpretability tools for machine learning
Kaur, H. et al · 2020
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Pathomic fusion: an integrated framework for fusing histopathology and genomic features for cancer diagnosis and prognosis
Chen, R. J. et al · 2020
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Debugging tests for model explanations
Adebayo, J., Muelly, M., Liccardi, I. & Kim, B · 2020
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Deep interpretability for gwas
Sharma, D. et al · 2020
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Probing ml models for fairness with the what-if tool and shap: hands-on tutorial
Wexler, J., Pushkarna, M., Robinson, S., Bolukbasi, T. & Zaldivar, A · 2020
Later among the works it cites.
Explaining quantitative measures of fairness
Lundberg, S. M · 2020
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Computationally derived image signature of stromal morphology is prognostic of prostate cancer recurrence following prostatectomy in african american patients
Bhargava, H. K. et al · 2020
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Adaptive sampling to reduce disparate performance
Abernethy, J., Awasthi, P., Kleindessner, M., Morgenstern, J. & Zhang, J · 2020
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Racial and ethnic health disparities related to covid-19
Lopez, L., Hart, L. H. & Katz, M. H · 2021
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Social determinants of health and health disparities: Covid-19 exposures and mortality among african american people in the united states
Maness, S. B. et al · 2021
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Race-free equations for egfr: Comparing effects on ckd classification
Diao, J. A., Powe, N. R. & Manrai, A. K · 2021
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Removing race from kidney function estimates
van der Burgh, A. C., Hoorn, E. J. & Chaker, L · 2021
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Removing race from kidney function estimates—reply
Diao, J. A., Powe, N. R. & Manrai, A. K · 2021
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An algorithmic approach to reducing unexplained pain disparities in underserved populations
Pierson, E., Cutler, D. M., Leskovec, J., Mullainathan, S. & Obermeyer, Z · 2021
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Moving beyond “algorithmic bias is a data problem”
Hooker, S · 2021
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Machine learning and algorithmic fairness in public and population health
Mhasawade, V., Zhao, Y. & Chunara, R · 2021
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The impact of site-specific digital histology signatures on deep learning model accuracy and bias
Howard, F. M. et al · 2021
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Do as ai say: susceptibility in deployment of clinical decision-aids
Gaube, S. et al · 2021
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Artificial intelligence/machine learning (ai/ml)–based software as a medical device (samd) action plan. january 2021 (2021)
Food, U., Administration, D. et al · 2021
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An empirical characterization of fair machine learning for clinical risk prediction
Pfohl, S. R., Foryciarz, A. & Shah, N. H · 2021
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Recommendations for Algorithmic Fairness Assessments of Predictive Models in Healthcare: Evidence from Large-scale Empirical Analyses
Pfohl, S. R · 2021
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Faircanary: Rapid continuous explainable fairness
Ghosh, A. & Shanbhag, A · 2021
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Robust fairness under covariate shift
Rezaei, A., Liu, A., Memarrast, O. & Ziebart, B. D · 2021
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Puyol-Anton, E. et al · 2021
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Targeting underrepresented populations in precision medicine: A federated transfer learning approach
Li, S., Cai, T. & Duan, R · 2021
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Explaining algorithmic fairness through fairness-aware causal path decomposition
Pan, W., Cui, S., Bian, J., Zhang, C. & Wang, F · 2021
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A patient-centric dataset of images and metadata for identifying melanomas using clinical context
Rotemberg, V. et al · 2021
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Ai fairness via domain adaptation
Joshi, N. & Burlina, P · 2021
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Radfusion: Benchmarking performance and fairness for multi-modal pulmonary embolism detection from ct and emr (2021)
Zhou, Y. et al · 2021
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Mimic-if: Interpretability and fairness evaluation of deep learning models on mimic-iv dataset
Meng, C., Trinh, L., Xu, N. & Liu, Y · 2021
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Fairlens: Auditing black-box clinical decision support systems
Panigutti, C., Perotti, A., Panisson, A., Bajardi, P. & Pedreschi, D · 2021
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Association of inclusion of more black individuals in lung cancer screening with reduced mortality
Prosper, A. E. et al · 2021
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The rsna pulmonary embolism ct dataset
Colak, E. et al · 2021
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Determining breast cancer biomarker status and associated morphological features using deep learning
Gamble, P. et al · 2021
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Deep learning in cancer pathology: a new generation of clinical biomarkers
Echle, A. et al · 2021
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Reading race: Ai recognises patient’s racial identity in medical images
Banerjee, I. et al · 2021
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Racial disparities in diagnostic delay among women with breast cancer
Miller-Kleinhenz, J. M. et al · 2021
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Systematic review of approaches to preserve machine learning performance in the presence of temporal dataset shift in clinical medicine
Guo, L. L. et al · 2021
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Fair machine learning under partial compliance
Dai, J., Fazelpour, S. & Lipton, Z · 2021
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Algorithms for fairness in sequential decision making
Wen, M., Bastani, O. & Topcu, U · 2021
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Embracing genetic diversity to improve black health (2021)
Oni-Orisan, A., Mavura, Y., Banda, Y., Thornton, T. A. & Sebro, R · 2021
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The pathophysiology of racial disparities
Calhoun, A · 2021
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It’s compaslicated: The messy relationship between rai datasets and algorithmic fairness benchmarks
Bao, M. et al · 2021
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Human-interpretable image features derived from densely mapped cancer pathology slides predict diverse molecular phenotypes
Diao, J. A. et al · 2021
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Federated learning for healthcare informatics
Xu, J. et al · 2021
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Beyond federated learning: fusion strategies for diabetic retinopathy screening algorithms trained from different device types
CHAKROBORTY, S., Patel, K. R. & Freytag, A · 2021
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End-to-end privacy preserving deep learning on multi-institutional medical imaging
Kaissis, G. et al · 2021
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Federated learning improves site performance in multicenter deep learning without data sharing
Sarma, K. V. et al · 2021
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Federated deep learning for detecting covid-19 lung abnormalities in ct: a privacy-preserving multinational validation study
Dou, Q. et al · 2021
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Federated semi-supervised learning for covid region segmentation in chest ct using multi-national data from china, italy, japan
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