AI is helping healthcare organisations determine care management programs and treatment plans – who gets what care – but these models and algorithms can be biased and introduce discrimination in the allocation or denial of care.
Read MoreThis guest panel series examines the use of AI in assisting healthcare, with a particular focus on automating tasks, communicating diagnoses and allocating resources. It examines the sources of bias in AI integrated systems and what we can do to eliminate it.
Read MoreThe double-edged sword of AI with bias; on the one hand it could treat every patient objectively and reduce bias, and on the other could impact certain patient populations adversely by using non-representative data. This video examines the potential of AI in reducing biases within medical diagnosis, by using AI technologies to understand how diseases […]
Read MoreThe advent of AI promises to revolutionise the way we think about medicine and healthcare, but who do we hold accountable when automated procedures go awry? In this talk, Varoon focuses on the lack of affordable medicines within healthcare and the concerns over racial bias being brought into the healthcare system.
Read MoreUsing the example of machine learning in medicine as an example, Rachel Thomas examines examples of racial bias within the AI technologies driving modern-day medicines and treatments. Rachel Thomas argues that whilst the diversity of your data set, and performance of your model across different demographic groups is important, this is only a narrow slice […]
Read MoreTalk 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.
Read MoreA 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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