Google Announces New AI App To Diagnose Skin Condititons

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This article discusses mobile apps that aid the self-diagnosis of skin conditions. The apps do intend to be inclusive of all skin types, however, the training data was revealed to contain only 3.5% of images for darker-skinned patients. Ninety per cent of the database was made up of people with fair skin, darker white skin, […]

The Potential for AI in healthcare

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This report discusses current applications of AI as well as potential future applications of AI in the healthcare system. The key categories of applications involve diagnosis and treatment recommendations, patient engagement and adherence, and administrative activities.

Addressing Bias: Artificial Intelligence in Cardiovascular Medicine

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Medical paper which examines the potential of Artificial Intelligence in cardiovascular medicine; it could hugely benefit patient diagnosis and treatment of what is the leading cause of morbidity and mortality worldwide. However, AI algorithms are still subject to their own biases, and predictive models might worsen health disparities through biases in the data training the […]

Debiasing artificial intelligence: Stanford researchers call for efforts to ensure that AI technologies do not exacerbate health care disparities

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Medical devices utilising AI technologies stand to reduce general biases in the health care system, however, if left unchecked, the technologies could unintentionally perpetuate sex, gender, and race biases. The AI devices rely on data-driven algorithms to inform health care decisions and aid in the diagnosis of diseases. After examining the biases inherent in these […]

Is a racially biased algorithm delaying healthcare for one million black people?

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An estimated one million black adults would be transferred earlier for kidney disease if US health systems removed a ‘race-based correction factor’ from an algorithm they use to diagnose people and decide whether to administer medication. There is a debate surrounding whether or not race-based correction should be removed, on the one hand, it perpetuates […]

If AI is going to be the world’s doctor, it needs better textbooks

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AI technologies are being used to diagnose Alzheimer’s disease by assessing speech. This technology could aid early diagnosis of Alzheimer’s. However, it’s evident that the algorithms behind this technology are trained on and for a specific tone of voice, excluding people of colour from the benefits of this technology.

Understanding Racial Bias in Medical AI Training Data

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AI-powered systems are being designed to support medical activities ranging from patient diagnosis and triaging to drug pricing. But when AI systems are trained on misrepresentative data sets they stand to develop discriminatory biases. Three case studies are explored that demonstrate the potential for racial bias in medical AI, including Melanoma Diagnosis and Diagnosis using […]

Does “AI” stand for augmenting inequality in the era of covid-19 healthcare?

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A team of medical ethics researchers are arguing that bias and discrimination within AI design and deployment risk exacerbating existing health inequity. The Covid-19 pandemic has disproportionately affected disadvantaged communities, and the uncritical deployment of AI in the fight against covid-19 risks amplifying the pandemic’s adverse effects on vulnerable groups by exhibiting racial biases. Although […]

The Challenge of AI Bias and Diverse Healthcare Data

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The 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 […]

Can we trust AI not to further embed racial bias and prejudice?

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Journalist Poppy Noor investigates how black people with melanoma are being underserved in healthcare, and the link to the racist algorithms driving new cancer software. Most of these algorithms use non-representative data, trained on majority white skin patients, resulting in black patients not being diagnosed.