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About Deep Learning For Identifying Metastatic Breast Cancer
This document describes a deep learning system that was used to identify metastatic breast cancer in whole slide images of lymph node biopsies. The system achieved state-of-the-art performance in two grand challenges, obtaining an AUC of 0.925 for whole slide image classification and a score of 0.7051 for tumor localization. A pathologist reviewing the same images obtained an AUC of 0.966 for classification and a score of 0.733. Combining the system's predictions with the pathologist's diagnoses increased the pathologist's classification performance to 0.995, representing an 85% reduction in human error. The system used a deep convolutional neural network trained on millions of image patches to perform classification and localization of cancer metastases at
Detailed Information
| Author: | ['Anderson erts'] |
|---|---|
| Publication Year: | 2021 |
| Pages: | 6 |
| Language: | English |
| Format: | |
| Price: | FREE |
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