Influence of Skin Type and Wavelength on Light Wave Reflectance

PPG sensors detecting changes in blood flow are assessed for effectiveness on dark and light skin tones. Studies have shown that green light lacks precision and accuracy, and may not read at all when measuring heart rate in darker skin types.
Accuracy in Wrist-Worn, Sensor-Based Measurements of Heart Rate and Energy Expenditure in a Diverse Cohort

This research paper assesses the accuracy of seven commercially available wrist-worn devices, which measure an individual’s heart rate and energy expenditure. The study shows, among other biases, that device error was higher for those with darker skin tones.
Use of AI-based tools for healthcare purposes: a survey study from consumers’ perspectives

This paper examines AI-based tools for healthcare from a consumer’s perspective. AI will be integral to our healthcare systems and will be integrated across several aspects of clinical care, with particular focus on care planning, this paper examines patients’ perspectives on the integration of AI into the healthcare system.
Does “AI” stand for augmenting inequality in the era of covid-19 healthcare?

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

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 […]
Assessing and Mitigating Bias in Medical Artificial Intelligence

Deep learning algorithms using data from homogeneous populations may be difficult to generalise, and potentially exacerbate racial disparities in health and health care. This research paper explores (1) whether the accuracy of a deep learning algorithm varies depending on race / ethnicity, and (2) whether this performance is down to racial variation or external health […]
Limiting racial disparities and bias for wearable devices in health science research

Consumer wearables are devices used for tracking activity, sleep and other health-related outcomes, intended to help people reach their wellness goals. However these wearables are less accurate for people with darker skin tones, this is especially worrying as these devices, and their data are being utilised in health-related research. Since skin tones affect algorithmic output.
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 […]
Does “AI” stand for augmenting inequality in the era of covid-19 healthcare?

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 pandemics adverse effects on vulnerable groups by exhibiting racial biases. Although […]
The Need for Use of Race Correction in Clinical Algorithms

Physicians still lack consensus on the meaning of race within medical science; there is an ongoing debate as to whether racial and ethnic categories can reflect underlying population genetics, and be clinically useful. Despite ongoing debates, this belief has become embedded within medical practice. This research paper examines how the algorithms used by clinicians to […]