According to a research team of the University of Pennsylvania and Penn's Perelman School of Medicine, an odor-based test can identify different cancer cells by sniffing vapors emanating from blood samples with up to 95% accuracy. The device is based on artificial intelligence and machine learning-based technology that helped deduce the blend of volatile organic compounds (VOCs) emitted by cells in blood plasma specimens. The results from the study indicated that the tool could be used as a non-invasive screening method for tumors that are difficult to identify, such as ovarian and pancreatic cancers.
The electronic olfaction system, or "e-nose," is equipped with nanosensors calibrated to detect the composition of VOCs, which are emitted by all cells. According to previous research, the VOCs emitted from tissue and plasma from ovarian cancer patients differ from those released from…
