AI technologies are being used to improve diagnosis within the healthcare system, by spotting early signs of disease, and determining the severity of patient needs. However, patients from marginalised groups are at risk of being misdiagnosed, and underserved in healthcare, as racially biased algorithms are less effective for non-white patients.

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Google Announces New AI App To Diagnose Skin Condititons

Earlier this week, Google announced the arrival of a new AI app to help diagnose skin conditions. It plans to launch it in Europe later this year. 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 […]

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Addressing Bias: Artificial Intelligence in Cardiovascular Medicine

Artificial intelligence (AI) is providing opportunities to transform cardiovascular medicine. As the leading cause of morbidity and mortality worldwide, cardiovascular disease is prevalent across all populations, with clear benefit to operationalise clinical and biomedical data to improve workflow… Medical paper which examines the potential of Artificial Intelligence in cardiovascular medicine; it could hugely benefit patient […]

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

Artificial intelligence in healthcare currently reflects the same racial and gender biases as the culture at large. Those prejudices are built into the data. 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 […]

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Understanding Racial Bias in Medical AI Training Data

By Adriana Krasniansky Interest in artificially intelligent (AI) health care has grown at an astounding pace: the global AI health care market is expected to reach $17.8 billion by 2025 and AI-powered systems are being designed to support medical activities ranging from patient diagnosis and… AI-powered systems are being designed to support medical activities ranging […]

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

Artificial intelligence can help tackle the covid-19 pandemic, but bias and discrimination in its design and deployment risk exacerbating existing health inequity argue David Leslie and colleagues. Among the most damaging characteristics of the covid-19 pandemic has been its disproportionate effect… A team of medical ethics researchers are arguing that bias and discrimination within AI […]

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The Challenge of AI Bias and Diverse Healthcare Data

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 […]

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

Heralded as an easy fix for health services under pressure, data technology is marching ahead unchecked. But is there a risk it could compound inequalities? Poppy Noor investigates. 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 […]

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AI-Driven Dermatology Could Leave Dark-Skinned Patients Behind

AI technologies have the potential to save thousands of people from skin cancer yearly, by aiding early diagnosis. However, this shift is also potentially dangerous for darker-skinned patients, as the demographic imbalances in dermatology can leave machine learning diagnoses less effective for darker-skinned patients.

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Google’s AI for mammograms doesn’t account for racial differences

A short article examining Google’s new AI for mammograms. It has hopes of replacing human radiologists with faster and more accurate diagnosis. However, there are worries over its accuracy in spotting cancer in diverse racial and ethnic populations, both due to white focused data sets and inherent biases within the healthcare system.

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AI reveals differences in appearance of cancer tissue between racial populations

Artificial Intelligence technologies are being used to understand potential differences in prostate cancer tissues between racial populations; cancer tissues manifest differently in black and white patients. This research is revealing the racial bias in AI systems used to diagnose prostate cancer. Algorithmic models are trained on data from majority white populations, which means that prostate […]

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Dissecting racial bias in an algorithm used to manage the health of populations

Research article examining racial bias in health algorithms. The research shows that a widely used algorithm, which affects millions of patients, exhibits a significant racial bias. There is evidence that Black patients, who are assigned the same level of risk as white patients by the algorithm, are actually much sicker. This racial discrimination is reducing […]

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New Study Blames Algorithm For Racial Discrimination

This article examines a tool created by Optum, which was designed to identify high-risk patients with untreated chronic diseases, in order to redistribute medical resources to those who need them most. Research has shown this algorithm to be biased; it was less likely to admit black people than white people who were equally sick to […]

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