Nuclear Morphology Is a Deep Learning Biomarker of Cellular Senescence

Using neural networks, investigators predicted senescence from the nuclear morphology of human fibroblasts with up to 95% accuracy, and investigated murine astrocytes, murine neurons, and fibroblasts with premature aging in culture.