Researcher address disparities in skin cancer detection

Adewole Adamson, MD, of the University of Texas, Austin, aims to create more equity in health care by collecting data from more diverse populations using artificial intelligence (AI), a type of machine learning. Dr. Adamson’s work is funded by the American Cancer Society (ACS), an organization committed to advancing health equity through research priorities, programs, and services for groups that have been marginalized.

Melanoma became a particular focus for Dr. Adamson after he met Avery Smith, who lost his wife, a black woman, to the deadly disease.

Avery Smith (left) and Adamson (side note)

This personal encounter, along with multiple conversations with black dermatology patients, led Dr. Adamson to a troubling discovery: As advanced as AI is in detecting possible skin cancers, it is highly biased.

To understand this bias, it helps to first understand how AI works in early skin cancer detection, which Dr. Adamson explains in his article for the New England Journal of Medicine (paywall). The process uses computers that draw on accumulated data sets to learn what healthy or unhealthy skin looks like and then creates an algorithm to predict diagnoses based on those data sets.

This process, known as supervised learningcould lead to huge benefits in preventive care.

After all, early detection is key to better results. The problem is that the data sets do not include enough information about darker skin tones. As Adamson put it, “everything is seen through a ‘white lens’.”

“If you don’t teach the algorithm with a diverse set of images, then that algorithm won’t work in the audience that is diverse,” Adamson writes in a study he co-authored with Smith (according to a story in the atlantic). “So there is a risk that people with skin of color will fall through the cracks.”

Tragically, Smith’s wife was diagnosed with melanoma too late and paid the ultimate price for it. And she was not an abnormality, although the disease is more common among white patients, black patients with cancer are much more likely to be diagnosed at later stages, causing a remarkable disparity in survival rates among non-Hispanic whites (90%) and non-Hispanic blacks (66%).

As a computer scientist, Smith was suspicious of this racial bias and approached Adamson, hoping that a black dermatologist would have more diverse data sets. Although Adamson did not have what Smith was initially looking for, this realization ignited a personal mission to investigate and reduce the disparities.

Now, Adamson is using the knowledge gained through his years of research to help advance the fight for health equity. For him, that means not only getting a broader range of data sets, but also having more conversations with patients to understand how socioeconomic status affects the level and efficiency of care.

“At the end of the day, what matters most is how we help patients at the patient level,” Adamson told Upworthy. “And how can you do that without knowing exactly what barriers they face?”

american cancer society, skin cancer treatment“What matters most is how we help patients at the patient level.”https://www.kellydavidsonstudio.com/

The American Cancer Society believes that everyone deserves a fair and just opportunity to prevent, find, treat, and survive cancer, regardless of how much money they make, the color of their skin, their sexual orientation, gender identity, disability status, or where. they live. Inclusive tools and resources can be found on the Health Equity section of their website. here. For more information on skin cancer, visit cancer.org/skincancer.

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