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The Growing Role of Digital Pathology and Machine Learning in Cancer Diagnostics (UCLA Case No. 2021-134)
Summary: Researchers at UCLA's Department of Radiological Sciences have developed an active learning methodology for digital pathology image analysis, addressing challenges posed by inconsistent annotations and revolutionizing the training of diagnostic algorithms. Background: The global digital pathology market is anticipated to experience significant...
Published: 8/9/2023
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Inventor(s):
Corey Arnold
,
Wenyuan Li
,
Jiayun Li
,
William Speier
Keywords(s):
active learning
,
Artifical Intelligence (Machine Learning, Data Mining)
,
Artificial Intelligence
,
Artificial Neural Network
,
artificial-intelligent materials
,
computational imaging task
,
convolutional networks
,
curriculum learning
,
Deep Learning
,
deep physical neural network
,
Digital Pathology
,
dynamic identification
,
Histopathological image analysis
,
histopathology images
,
Image Processing
,
Magnetic Resonance Imaging Pathology
,
Medical Devices and Materials
,
Medical Imaging
,
noisy annotations
,
noisy label detection
,
pathology image analysis
Category(s):
Software & Algorithms
,
Software & Algorithms > Image Processing
,
Electrical > Imaging
,
Medical Devices > Medical Imaging