Modern Medicines and treatments can be improved with the progression of AI in medicine by discovering new drugs, personalising treatments, and speeding up chemical trials. But if the racial exclusion common in biomedical research seeps into the data behind AI there’s a risk that these medicines won’t be effective for everyone.
New research shows that AI models designed for health care settings can exhibit bias against certain ethnic and gender groups. Machine learning models for healthcare hold promise in improving medical treatments by improving predictions of care and mortality, however their black box nature, and bias in training data sets leaves them vulnerable to instead hinder […]
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Talk by Rachel Thomas on the prevalence of bias within AI-based technology used in medicine. AI has the potential to remove human biases in the healthcare system, however its integration within medicine could also amplify the existing biases.
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A short video examining the lack of inclusion within clinical biomedical research, and the consequence this has on the effectiveness of the treatments and medicines for non-white patients. Lack of research on minority patients means that we do not understand the racial differences in drug response, and so approved medical treatments are excluding a huge […]
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By Amber Roguski. This is the second post in a two-part blog series. It explores the under-representation of Minority Ethnic individuals as participants in biomedical research. This article explores racial bias and exclusion within biomedical research. White People are 87% more likely to be included in medical research than people from a Minority Ethnic Background, […]
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