Deep learning-based research on the influence of training data size for breast cancer pathology detection

Deep learning-based research on the influence of training data size for breast cancer pathology detection

In pathological diagnosis of breast cancer, there are problems such as shortage of pathologists, difficulties in sample labeling, and huge workload of manual diagnosis. Therefore, deep learning-based computer-assisted pathology analysis systems have been developed to diagnose breast cancer and have...

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Bibliographic Details
Main Authors: Chongyang Cui, Shangchun Fan, Han Lei, Xiaolei Qu, Dezhi Zheng
Format: Article
Language:English
Published: Wiley 2019-12-01
Series:The Journal of Engineering
Subjects:
feature extraction
learning (artificial intelligence)
medical image processing
patient diagnosis
cancer
neural nets
image classification
training data set
training set
pathology computer-assisted breast cancer analysis system
different pathological images
training data size
breast cancer pathology detection
pathological diagnosis
deep learning-based computer-assisted pathology analysis systems
Online Access:https://digital-library.theiet.org/content/journals/10.1049/joe.2018.9093

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https://digital-library.theiet.org/content/journals/10.1049/joe.2018.9093

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