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Improving model fairness in image-based computer-aided diagnosis
4 references·0 citing·18 second hop
Improving model fairness in image-based computer-aided diagnosis (2023)Improving model fairness in image-based c…FairPrune: Achieving Fairness Through Pruning for Dermatological Disease Diagnosis (2022)FairPrune: Achieving Fairness…A Survey on Bias and Fairness in Machine Learning (2021)A Survey on Bias and Fairness…Fairness without Demographics through Adversarially Reweighted Learning (2020)Fairness without Demographics…Dissecting racial bias in an algorithm used to manage the health of populations (2019)Dissecting racial bias in an …Fairness through awareness (2012)Semantics derived automatically from language corpora contain human-like biases (2017)Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification (2018)Algorithmic Bias in Education (2021)Connecting the dots in trustworthy Artificial Intelligence: From AI principles, ethics, and key requirements to responsible AI systems and regulation (2023)Fairness and Bias in Artificial Intelligence: A Brief Survey of Sources, Impacts, and Mitigation Strategies (2023)Big Data's Disparate Impact (2014)Fair Prediction with Disparate Impact: A Study of Bias in Recidivism Prediction Instruments (2017)Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence (2020)Addressing bias in big data and AI for health care: A call for open science (2021)Justice as Fairness: A Restatement (2002)Algorithmic fairness datasets: the story so far (2022)Towards Fair Classifiers Without Sensitive Attributes (2022)A Survey on Intersectional Fairness in Machine Learning: Notions, Mitigation, and Challenges (2023)Data preprocessing techniques for classification without discrimination (2011)Men Also Like Shopping: Reducing Gender Bias Amplification using Corpus-level Constraints (2017)Mitigating Unwanted Biases with Adversarial Learning (2018)FairAdaBN: Mitigating Unfairness with Adaptive Batch Normalization and Its Application to Dermatological Disease Classification (2023)
this work references cited by second hop

References

  • 2019Dissecting racial bias in an algorithm used to manage the health of populations7,086 cited
  • 2021A Survey on Bias and Fairness in Machine Learning5,798 cited
  • 2020Fairness without Demographics through Adversarially Reweighted Learning117 cited
  • 2022FairPrune: Achieving Fairness Through Pruning for Dermatological Disease Diagnosis50 cited

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