Write it like you see it: Detectable differences in clinical notes by race lead to differential model recommendations
Clinical notes are becoming an increasingly important data source for machine learning
(ML) applications in healthcare. Prior research has shown that deploying ML models can …
(ML) applications in healthcare. Prior research has shown that deploying ML models can …
Coding Inequity: Assessing GPT-4's Potential for Perpetuating Racial and Gender Biases in Healthcare
Background. Large language models (LLMs) such as GPT-4 hold great promise as
transformative tools in healthcare, ranging from automating administrative tasks to …
transformative tools in healthcare, ranging from automating administrative tasks to …
Interpretable bias mitigation for textual data: Reducing genderization in patient notes while maintaining classification performance
Medical systems in general, and patient treatment decisions and outcomes in particular, can
be affected by bias based on gender and other demographic elements. As language models …
be affected by bias based on gender and other demographic elements. As language models …
Hurtful words: quantifying biases in clinical contextual word embeddings
In this work, we examine the extent to which embeddings may encode marginalized
populations differently, and how this may lead to a perpetuation of biases and worsened …
populations differently, and how this may lead to a perpetuation of biases and worsened …
Human evaluation and correlation with automatic metrics in consultation note generation
In recent years, machine learning models have rapidly become better at generating clinical
consultation notes; yet, there is little work on how to properly evaluate the generated …
consultation notes; yet, there is little work on how to properly evaluate the generated …
Reading race: AI recognises patient's racial identity in medical images
Background: In medical imaging, prior studies have demonstrated disparate AI performance
by race, yet there is no known correlation for race on medical imaging that would be obvious …
by race, yet there is no known correlation for race on medical imaging that would be obvious …
Large language models propagate race-based medicine
Large language models (LLMs) are being integrated into healthcare systems; but these
models may recapitulate harmful, race-based medicine. The objective of this study is to …
models may recapitulate harmful, race-based medicine. The objective of this study is to …
Assessing the potential of GPT-4 to perpetuate racial and gender biases in health care: a model evaluation study
Summary Background Large language models (LLMs) such as GPT-4 hold great promise as
transformative tools in health care, ranging from automating administrative tasks to …
transformative tools in health care, ranging from automating administrative tasks to …
Negative Patient Descriptors: Documenting Racial Bias In The Electronic Health Record: Study examines racial bias in the patient descriptors used in the electronic …
M Sun, T Oliwa, ME Peek, EL Tung - Health Affairs, 2022 - healthaffairs.org
Little is known about how racism and bias may be communicated in the medical record. This
study used machine learning to analyze electronic health records (EHRs) from an urban …
study used machine learning to analyze electronic health records (EHRs) from an urban …
Artificial intelligence and bias: a scoping review
AI bias has been reported in many areas, including business (Manyika, 2019; Manyika et al.,
2019), social media (Nouri, 2021), the economy (Omowole, 2021), politics (Kumawat, 2020) …
2019), social media (Nouri, 2021), the economy (Omowole, 2021), politics (Kumawat, 2020) …