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The aim is to provide a publicly available dataset for the automated classification of breast cancer histopathology images.

A Dataset for Breast Cancer Histopathological Image Classification

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The aim is to provide a publicly available dataset for the automated classification of breast cancer histopathology images.
Introduced a dataset of 7909 breast cancer histopathology images from 82 patients.
Included both benign and malignant images for classification tasks.
Demonstrated preliminary results from state-of-the-art image classification systems with accuracy between 80% to 85%.
The accuracy of the automated classification ranged from 80% to 85%.
The dataset is intended to support the development of computer-aided diagnosis tools.
Standardized evaluation protocols were provided to facilitate comparisons among methods.

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Dataset introduces automated classification of breast cancer images, aiming to enhance clinical diagnosis.

Spanhol et al. (2015) studied this question.

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