Using machine learning, an electronic nose can "smell" early signs of ovarian cancer in the blood.
The method is precise and, according to the LiU researchers behind the study, it could eventually be used to find many different cancers.
The study is published in the scientific journal Advanced intelligent systems.
The method developed by the researchers does not need the identification of a specific biomarker.
Instead, the electronic nose picks up a large variety of volatile substances emitted from blood plasma samples.
The data are then analysed using advanced machine-learning models to identify patterns specific to, in this case, ovarian cancer.
The models are trained on known samples from a biobank. The tool has 97 percent accuracy.
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