New e-nose spots hard-to-detect forms of cancer

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AI and machine learning have been combined to create an 'e-nose' that can identify hard-to-detect forms of cancer with up to 95 percent accuracy. 

The odour-based test sniffs out vapours emanating from blood samples and was able to distinguish between benign and pancreatic and ovarian cancer cells, according to a new study from researchers at the University of Pennsylvania and Penn's Perelman School of Medicine.

Developed at Penn, the non-invasive tool uses artificial intelligence and machine learning to decipher the mixture of volatile organic compounds (VOCs) emitting off cells in blood plasma samples.

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The results will be presented at the annual American Society of Clinical Oncology meeting on June 4, 2021 by A. T. Charlie Johnson, PhD, the Rebecca W. Bushnell Professor of Physics and Astronomy in Penn's School of Arts & Sciences.

"It's an early study but the results are very promising," Johnson said in a statement. "The data shows we can identify these tumours at both advanced and the earliest stages, which is exciting. If developed appropriately for the clinical setting, this could potentially be a test that's done on a standard blood draw that may be part of your annual physical."

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