A predicted-loss based active learning approach for robust cancer pathology image analysis in the workplace

A predicted-loss based active learning approach for robust cancer pathology image analysis in the workplace

Abstract Background Convolutional neural network-based image processing research is actively being conducted for pathology image analysis. As a convolutional neural network model requires a large amount of image data for training, active learning (AL) has been developed to produce efficient learning...

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Bibliographic Details
Main Authors: Mujin Kim, Willmer Rafell Quiñones Robles, Young Sin Ko, Bryan Wong, Sol Lee, Mun Yong Yi
Format: Article
Language:English
Published: BMC 2024-01-01
Series:BMC Medical Imaging
Subjects:
Active learning strategy
Noisy data
Cancer pathology images
Convolutional neural networks
Deep learning
Histopathology image analysis
Online Access:https://doi.org/10.1186/s12880-023-01170-8

Internet

https://doi.org/10.1186/s12880-023-01170-8

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