AI Medical Compendium Topic:
Breast Neoplasms

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Fourier ptychographic and deep learning using breast cancer histopathological image classification.

Journal of biophotonics
Automated, as well as accurate classification with breast cancer histological images, was crucial for medical applications because of detecting malignant tumors via histopathological images. In this work create a Fourier ptychographic (FP) and deep l...

Gigapixel end-to-end training using streaming and attention.

Medical image analysis
Current hardware limitations make it impossible to train convolutional neural networks on gigapixel image inputs directly. Recent developments in weakly supervised learning, such as attention-gated multiple instance learning, have shown promising res...

Transcriptional intra-tumour heterogeneity predicted by deep learning in routine breast histopathology slides provides independent prognostic information.

European journal of cancer (Oxford, England : 1990)
BACKGROUND: Intra-tumour heterogeneity (ITH) causes diagnostic challenges and increases the risk for disease recurrence. Quantification of ITH is challenging and has not been demonstrated in large studies. It has previously been shown that deep learn...

Consistency of Artificial Intelligence (AI)-based Diagnostic Support Software in Short-term Digital Mammography Reimaging After Core Needle Biopsy.

Journal of digital imaging
To evaluate the consistency in the performance of Artificial Intelligence (AI)-based diagnostic support software in short-term digital mammography reimaging after core needle biopsy. Of 276 women who underwent short-term (<3 mo) serial digital mammog...

Deep learning to automatically evaluate HER2 gene amplification status from fluorescence in situ hybridization images.

Scientific reports
Human epidermal growth factor receptor 2 (HER2) gene amplification helps identify breast cancer patients who may respond to targeted anti-HER2 therapy. This study aims to develop an automated method for quantifying HER2 fluorescence in situ hybridiza...

Interpretable HER2 scoring by evaluating clinical guidelines through a weakly supervised, constrained deep learning approach.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
The evaluation of the Human Epidermal growth factor Receptor-2 (HER2) expression is an important prognostic biomarker for breast cancer treatment selection. However, HER2 scoring has notoriously high interobserver variability due to stain variations ...

Controversies and strengths of robot-assisted mastectomy.

European journal of cancer prevention : the official journal of the European Cancer Prevention Organisation (ECP)
Nipple-sparing mastectomy (NSM) is used to improve cosmetic outcomes while maintaining oncological safety in patients with early breast cancer; however, NSM requires a higher level of skill and workload than mastectomy and is associated with long, vi...

CONFIDENT-trial protocol: a pragmatic template for clinical implementation of artificial intelligence assistance in pathology.

BMJ open
INTRODUCTION: Artificial intelligence (AI) has been on the rise in the field of pathology. Despite promising results in retrospective studies, and several CE-IVD certified algorithms on the market, prospective clinical implementation studies of AI ha...

Deep learning for predicting future lesion emergence in high-risk breast MRI screening: a feasibility study.

European radiology experimental
BACKGROUND: International societies have issued guidelines for high-risk breast cancer (BC) screening, recommending contrast-enhanced magnetic resonance imaging (CE-MRI) of the breast as a supplemental diagnostic tool. In our study, we tested the app...