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Carcinoma in Situ

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Prediction of Occult Invasive Disease in Ductal Carcinoma in Situ Using Deep Learning Features.

Journal of the American College of Radiology : JACR
PURPOSE: The aim of this study was to determine whether deep features extracted from digital mammograms using a pretrained deep convolutional neural network are prognostic of occult invasive disease for patients with ductal carcinoma in situ (DCIS) o...

Breast cancer histopathology image classification through assembling multiple compact CNNs.

BMC medical informatics and decision making
BACKGROUND: Breast cancer causes hundreds of thousands of deaths each year worldwide. The early stage diagnosis and treatment can significantly reduce the mortality rate. However, the traditional manual diagnosis needs intense workload, and diagnosti...

Assessing the impact of deep-learning assistance on the histopathological diagnosis of serous tubal intraepithelial carcinoma (STIC) in fallopian tubes.

The journal of pathology. Clinical research
In recent years, it has become clear that artificial intelligence (AI) models can achieve high accuracy in specific pathology-related tasks. An example is our deep-learning model, designed to automatically detect serous tubal intraepithelial carcinom...