(AI) Skin in the Game

When devastating diseases manifest themselves, patients want answers – fast. Unfortunately, those are not always forthcoming, especially with conditions such as epidermolysis bullosa acquisita (EBA), an autoimmune blistering disease in which antibodies attack type VII collagen in the skin’s epidermal basement membrane.

Currently, the disease can take months or years to diagnose, partly because diagnostic antibody patterns can be difficult to identify on a skin biopsy slide. To address the problem, dermatologist Joost Meijer and colleagues designed an AI-based system to spot the serrated, U-shaped immunodeposition patterns characteristic of the disease (1).

The system yielded sensitivity and specificity of 89.3 percent – outperforming many doctors – but the work is still ongoing. “It will take a year to collect the data of new skin biopsies, which will be able to validate the system,” said Meijer (2). “Hopefully, we will then have a quicker and easier way to diagnose EBA and prevent the sometimes debilitating scarring.”

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References

1. C Shi et al., Am J Pathol, [Online ahead of print] (2021). PMID: 34197776.
2. University of Groningen (2021). Available at: https://bit.ly/3feYUho.

About the Author(s)

Michael Schubert

While obtaining degrees in biology from the University of Alberta and biochemistry from Penn State College of Medicine, I worked as a freelance science and medical writer. I was able to hone my skills in research, presentation and scientific writing by assembling grants and journal articles, speaking at international conferences, and consulting on topics ranging from medical education to comic book science. As much as I’ve enjoyed designing new bacteria and plausible superheroes, though, I’m more pleased than ever to be at Texere, using my writing and editing skills to create great content for a professional audience.

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