AI-Based Blood Test Detects the Earliest Signs of Breast Cancer
A new study by researchers at the University of Edinburgh reveals a groundbreaking screening method that combines laser analysis with artificial intelligence, marking the first of its kind to identify patients in the early stages of breast cancer.
The research team states that this fast and non-invasive technique detects subtle changes in blood flow during the initial stages of the disease, known as Stage 1a, which are undetectable with current testing methods.
Using this innovative method, researchers successfully identified early-stage breast cancer by optimizing a laser analysis technique – known as Raman spectroscopy – and integrating it with machine learning, a type of artificial intelligence.
The method works by directing a laser beam onto blood plasma samples taken from patients. The properties of light, after interacting with the blood, are analyzed using a device called a spectrometer to uncover small changes in the chemical composition of cells and tissues that signal early signs of the disease.
In a preliminary study involving 12 samples from breast cancer patients and 12 healthy individuals, this method achieved a 98% success rate in detecting breast cancer at Stage 1a. The test also distinguished between each of the four main subgroups of breast cancer with over 90% accuracy, enabling patients to receive more effective and personalized treatment.
