Researchers at the University of California, Los Angeles (UCLA) have developed an uncertainty-aware computational pathology platform that combines lensfree holographic imaging with deep learning to perform automated HER2 assessment in breast cancer tissue samples. The paper is published in the journal BME Frontiers.

HER2 (human epidermal growth factor receptor 2) is an important biomarker used in breast cancer diagnosis and treatment planning. Accurate HER2 scoring is essential because it directly influences therapeutic decisions and patient management.