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2022-140 Label-Free Virtual HER2 Immunohistochemical Staining of Breast Tissue Using Deep Learning

SUMMARY: UCLA researchers in the Departments of Bioengineering and Electrical and Computer Engineering have developed a deep learning-based algorithm that can detect and quantify the breast cancer marker human epidermal growth factor receptor 2 (HER2) in microscopic images without the need for time-consuming immunohistochemical staining (IHC). BACKGROUND:...

Published: 4/9/2024 | Inventor(s): Aydogan Ozcan, Yair Rivenson, Bijie Bai, Hongda Wang

Keywords(s): Artifical Intelligence (Machine Learning, Data Mining), Biomarker, Bladder Cancer, Breast Cancer, Cancer, Cancer Immunotherapy, Computer Aided Learning, Diagnostic Markers & Platforms, Diagnostic Test, Fluorescence, Fluorescent Labelling, HER2/Neu, Histology, Immune System, Immunohistochemistry, Life Science Research Tools, Machine Learning, Optics, Research Methods, Unsupervised Learning

Category(s): Life Science Research Tools, Life Science Research Tools > Research Methods, Diagnostic Markers, Diagnostic Markers > Immunology, Medical Devices > Medical Imaging, Medical Devices > Medical Imaging > Fluorescence, Software & Algorithms > Artificial Intelligence & Machine Learning, Optics & Photonics