Search Results - unsupervised+learning

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Stain-Free, Rapid, and Quantitative Viral Plaque Assay Using Deep Learning and Holography (Case No. 2022-326)
Intro Sentence: UCLA researchers in the Department of Electrical and Computer Engineering have developed a rapid and stain-free quantitative assay using lens-free holography and deep learning to efficiently and cost-effectively determine the presence of viral plaque-forming units (PFUs) in samples. Background: A broad range of viruses have caused...
Published: 10/17/2024   |   Inventor(s): Aydogan Ozcan, Yuzhu Li, Tairan Liu
Keywords(s): Antiviral Drug, Artifical Intelligence (Machine Learning, Data Mining), Assay, Bioassay, Computer Aided Learning, Diagnostic Markers & Platforms, Diagnostic Platform Technologies (E.G. Microfluidics), Diagnostic Test, Digital Holography, Electrical, Electrical Brain Stimulation, Electrical Breakdown, Electrical Engineering, Electrical Impedance, Electrical Load, Electrical Load Equation Of State, Electrical Resistance And Conductance, Electrical Resistivity And Conductivity, Holography, Immunoassay, Immunoassay Sense (Molecular Biology), Lentivirus Viral Vector, Machine Learning, Machine Learning Autonomous Car Gradient Descent, Machine Learning Pain Management, Machine Learning Particulates Global Climate Model, Network Analysis (Electrical Circuits), Perceptual Learning, Plasmid Trabecular Meshwork Aqueous Humour Viral Vector, Targets And Assays, Transcutaneous Electrical Nerve Stimulation, Transfection Viral Vector, Unsupervised Learning , Viability Assay, Viral Delivery Systems, Viral Envelope, Viral Load
Category(s): Diagnostic Markers, Diagnostic Markers > Targets And Assays, Electrical, Life Science Research Tools, Life Science Research Tools > Research Methods, Life Science Research Tools > Other Reagents, Software & Algorithms > Artificial Intelligence & Machine Learning
2019-737 Deep Learning-Based Color Holographic Microscopy
Summary: UCLA researchers in the Department of Electrical Engineering have developed a novel deep learning-based method that performs high-fidelity color image reconstruction using a single hologram. Background: Pathology slides are currently the gold standard in diagnostics for many diseases. Accurate color representations of well stained pathology...
Published: 7/19/2023   |   Inventor(s): Aydogan Ozcan, Yair Rivenson, Tairan Liu, Yibo Zhang, Zhensong Wei
Keywords(s): Artifical Intelligence (Machine Learning, Data Mining), Artificial Neural Network, Computer Aided Learning, Confocal Microscopy, Cytopathology, Digital Holography, Electron Microscope, Fluorescence Microscope, Fluorescence-Lifetime Imaging Microscopy Leading Lights, Histology, Histopathology, Holography, Image Resolution, Imaging, Immunohistochemistry, Machine Learning, Magnetic Resonance Imaging Pathology, Medical Imaging, Microscope, Microscopy, Microscopy And Imaging, Neuropathology, Pathogen, Pathogenesis, Pathophysiology, Perceptual Learning, Unsupervised Learning , Wavelength
Category(s): Electrical, Electrical > Imaging, Life Science Research Tools, Life Science Research Tools > Microscopy And Imaging, Software & Algorithms, Software & Algorithms > Artificial Intelligence & Machine Learning, Diagnostic Markers, Medical Devices > Medical Imaging
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