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Toward fair medical advice: Addressing and mitigating bias in large language model-based healthcare applications
9 references·0 citing·43 second hop
Toward fair medical advice: Addressing and mitigating bias in large language model-based healthcare applications (2025)Toward fair medical advice: Addressing an…The life cycle of large language models in education: A framework for understanding sources of bias (2024)The life cycle of large langu…Large language models in law: A survey (2024)Large language models in law:…Bias and Fairness in Large Language Models: A Survey (2024)Bias and Fairness in Large La…Large Language Model as Attributed Training Data Generator: A Tale of Diversity and Bias (2023)Large Language Model as Attri…Fairness in Machine Learning: A Survey (2023)Fairness in Machine Learning:…Bias Mitigation for Machine Learning Classifiers: A Comprehensive Survey (2023)Bias Mitigation for Machine L…Social bias, discrimination and inequity in healthcare: mechanisms, implications and recommendations (2022)Social bias, discrimination a…A Review on Fairness in Machine Learning (2022)A Review on Fairness in Machi…Societal Biases in Language Generation: Progress and Challenges (2021)Societal Biases in Language G…CRITICAL QUESTIONS FOR BIG DATA (2012)Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification (2018)A Survey on Bias and Fairness in Machine Learning (2021)An Overview of Artificial Intelligence Ethics (2022)Trustworthy AI: From Principles to Practices (2022)Considerations for addressing bias in artificial intelligence for health equity (2023)Fairness through awareness (2012)Equality of Opportunity in Supervised Learning (2016)Language (Technology) is Power: A Critical Survey of “Bias” in NLP (2020)Harms of Gender Exclusivity and Challenges in Non-Binary Representation in Language Technologies (2021)The Sociodemographic Biases in Machine Learning Algorithms: A Biomedical Informatics Perspective (2024)The Dark Side of AI Companionship: A Taxonomy of Harmful Algorithmic Behaviors in Human-AI Relationships (2025)Measuring individual differences in implicit cognition: The implicit association test. (1998)Measuring individual differences in implicit cognition: The implicit association test. (1998)Implicit Racial/Ethnic Bias Among Health Care Professionals and Its Influence on Health Care Outcomes: A Systematic Review (2015)Data and model bias in artificial intelligence for healthcare applications in New Zealand (2022)Beyond ideals: why the (medical) AI industry needs to motivate behavioural change in line with fairness and transparency values, and how it can do it (2023)The cultural stereotype and cultural bias of ChatGPT (2025)Big Data's Disparate Impact (2014)Bias and Unfairness in Machine Learning Models: A Systematic Review on Datasets, Tools, Fairness Metrics, and Identification and Mitigation Methods (2023)Fairness in recommender systems: research landscape and future directions (2023)Mental-LLM (2024)Finite-time Analysis of the Multiarmed Bandit Problem (2002)Dissecting racial bias in an algorithm used to manage the health of populations (2019)A Comprehensive Empirical Study of Bias Mitigation Methods for Machine Learning Classifiers (2023)A Comprehensive Review of Bias in Deep Learning Models: Methods, Impacts, and Future Directions (2024)Policy advice and best practices on bias and fairness in AI (2024)HISTORIAE, History of Socio-Cultural Transformation as Linguistic Data Science. A Humanities Use Case (2019)Aion Framework: Dimensional Emergence of AI Consciousness, Observer-Induced Collapse, and Cosmological Portal Dynamics (2023)Towards trustworthy LLMs: a review on debiasing and dehallucinating in large language models (2024)A survey on LLM-as-a-judge (2026)Semantics derived automatically from language corpora contain human-like biases (2017)Advancing equity and inclusion in educational practices with AI ‐powered educational decision support systems ( AI ‐ EDSS ) (2024)Beyond principlism: practical strategies for ethical AI use in research practices (2024)To use or not to use? Generative AI adoption in Chinese business schools (2025)2013 IEEE International Conference on Big Data (2013)On the Opportunities and Risks of Foundation Models (2021)CBR-RAG: Case-Based Reasoning for Retrieval Augmented Generation in LLMs for Legal Question Answering (2024)Augmenting Geospatial Data With Large Language Models Using Compositional Attention for Improved Avian Mobility Tasks Prediction (2025)Deconstructing the ethics of large language models from long-standing issues to new-emerging dilemmas: a survey (2025)A Comparative Analysis to Evaluate Bias and Fairness Across Large Language Models with Benchmarks (2024)Bias Testing and Mitigation in LLM-based Code Generation (2025)Conceptualizing and Operationalizing Prompt Literacy for English Language Learners (2025)
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References

  • 2024Bias and Fairness in Large Language Models: A Survey741 cited
  • 2023Fairness in Machine Learning: A Survey645 cited
  • 2022A Review on Fairness in Machine Learning596 cited
  • 2023Bias Mitigation for Machine Learning Classifiers: A Comprehensive Survey222 cited
  • 2024Large language models in law: A survey151 cited
  • 2021Societal Biases in Language Generation: Progress and Challenges131 cited
  • 2024The life cycle of large language models in education: A framework for understanding sources of bias118 cited
  • 2023Large Language Model as Attributed Training Data Generator: A Tale of Diversity and Bias109 cited
  • 2022Social bias, discrimination and inequity in healthcare: mechanisms, implications and recommendations70 cited

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