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PHILADELPHIA An odor-based test that sniffs out vapors emanating from blood samples was able to distinguish between benign and pancreatic and ovarian cancer cells with up to 95 percent accuracy, according to a new study from researchers at the
University of Pennsylvania and
Penn s Perelman School of Medicine.
The findings suggest that the Penn-developed tool which uses artificial intelligence and machine learning to decipher the mixture of volatile organic compounds (VOCs) emitting off cells in blood plasma samples could serve as a non-invasive approach to screen for harder-to-detect cancers, such as pancreatic and ovarian.
The results will be presented at the annual