Learning where to see: a novel attention model for automated immunohistochemical scoring

T Qaiser, NM Rajpoot - IEEE transactions on medical imaging, 2019 - ieeexplore.ieee.org
Estimating over-amplification of human epidermal growth factor receptor 2 (HER2) on
invasive breast cancer is regarded as a significant predictive and prognostic marker. We …

[HTML][HTML] The utility of a deep learning-based approach in Her-2/neu assessment in breast cancer

S Kabir, S Vranic, RM Al Saady, MS Khan… - Expert Systems with …, 2024 - Elsevier
Introduction HER-2/neu is a protein present on the surface of specific cancer cells and has
been linked to the development and progression of certain cancer types. It is present in 15 to …

Weakly-supervised classification of HER2 expression in breast cancer haematoxylin and eosin stained slides

SP Oliveira, J Ribeiro Pinto, T Gonçalves… - Applied Sciences, 2020 - mdpi.com
Featured Application This work finds its key application in medical diagnosis and prognosis.
It paves the way to robust automatic HER2 classification using only H&E slides. This …

Active and incremental learning with weak supervision

CA Brust, C Käding, J Denzler - KI-Künstliche Intelligenz, 2020 - Springer
Large amounts of labeled training data are one of the main contributors to the great success
that deep models have achieved in the past. Label acquisition for tasks other than …

Automated molecular subtyping of breast carcinoma using deep learning techniques

S Niyas, R Bygari, R Naik, B Viswanath… - IEEE Journal of …, 2023 - ieeexplore.ieee.org
Objective: Molecular subtyping is an important procedure for prognosis and targeted therapy
of breast carcinoma, the most common type of malignancy affecting women …

Mimicking a pathologist: dual attention model for scoring of gigapixel histology images

M Raza, R Awan, RMS Bashir, T Qaiser… - arXiv preprint arXiv …, 2023 - arxiv.org
Some major challenges associated with the automated processing of whole slide images
(WSIs) includes their sheer size, different magnification levels and high resolution. Utilizing …

[引用][C] Learning where to see next: Attention model for automated immunohistochemical scoring