Researchers at City of Hope, a cancer research and treatment organization in Los Angeles, and the University of California, Berkeley, have developed a pioneering machine-learning platform called MechanoAge, which assesses breast cancer risk by examining the mechanical properties of individual breast cells. The study, published in the journal Lancet’s eBioMedicine, reveals that a cell's 'mechanical age' can indicate cancer risk, especially for women without known genetic predispositions. Traditional risk assessment methods often rely on population models or breast density measurements, which can be inaccurate. MechanoAge addresses this gap by providing quantifiable data derived from the physical behavior of cells under stress. The platform utilizes a microfluidic device that squeezes individual breast epithelial cells, measuring their deformation and recovery. This innovative approach allows researchers to calculate a breast cancer risk score based on mechanical properties, offering a more personalized assessment. The AI algorithm developed can accurately identify women at high risk, including those with genetic mutations, and has the potential to revolutionize breast cancer screening by providing tangible evidence for women to discuss with their healthcare providers. This collaboration between City of Hope and UC Berkeley has spanned over 12 years, combining expertise in engineering and cancer biology to achieve these significant findings.