One label is all you need: Interpretable AI-enhanced histopathology for oncology

TE Tavolara, Z Su, MN Gurcan, MKK Niazi - Seminars in Cancer Biology, 2023 - Elsevier
Artificial Intelligence (AI)-enhanced histopathology presents unprecedented opportunities to
benefit oncology through interpretable methods that require only one overall label per …

CAD systems for colorectal cancer from WSI are still not ready for clinical acceptance

SP Oliveira, PC Neto, J Fraga, D Montezuma… - Scientific Reports, 2021 - nature.com
Most oncological cases can be detected by imaging techniques, but diagnosis is based on
pathological assessment of tissue samples. In recent years, the pathology field has evolved …

NSGA-II-DL: metaheuristic optimal feature selection with deep learning framework for HER2 classification in breast cancer

J Majidpour, TA Rashid, R Thinakaran… - IEEE …, 2024 - ieeexplore.ieee.org
Immunohistochemistry (IHC) slides are graded for breast cancer based on visual markers
and morphological characteristics of stained membrane regions. The usage of whole slide …

[HTML][HTML] Strategies for enhancing the multi-stage classification performances of her2 breast cancer from hematoxylin and eosin images

MSH Shovon, MJ Islam, MNAK Nabil, MM Molla… - Diagnostics, 2022 - mdpi.com
Breast cancer is a significant health concern among women. Prompt diagnosis can diminish
the mortality rate and direct patients to take steps for cancer treatment. Recently, deep …

Analyzing histological images using hybrid techniques for early detection of multi-class breast Cancer based on fusion features of CNN and handcrafted

M Al-Jabbar, M Alshahrani, EM Senan, IA Ahmed - Diagnostics, 2023 - mdpi.com
Breast cancer is the second most common type of cancer among women, and it can threaten
women's lives if it is not diagnosed early. There are many methods for detecting breast …

An interpretable machine learning system for colorectal cancer diagnosis from pathology slides

PC Neto, D Montezuma, SP Oliveira, D Oliveira… - NPJ precision …, 2024 - nature.com
Considering the profound transformation affecting pathology practice, we aimed to develop
a scalable artificial intelligence (AI) system to diagnose colorectal cancer from whole-slide …

[HTML][HTML] iMIL4PATH: A semi-supervised interpretable approach for colorectal whole-slide images

PC Neto, SP Oliveira, D Montezuma, J Fraga… - Cancers, 2022 - mdpi.com
Simple Summary Nowadays, colorectal cancer is the third most incident cancer worldwide
and, although it can be detected by imaging techniques, diagnosis is always based on …

HAHNet: a convolutional neural network for HER2 status classification of breast cancer

J Wang, X Zhu, K Chen, L Hao, Y Liu - BMC bioinformatics, 2023 - Springer
Objective Breast cancer is a significant health issue for women, and human epidermal
growth factor receptor-2 (HER2) plays a crucial role as a vital prognostic and predictive …

HER2GAN: Overcome the scarcity of HER2 breast cancer dataset based on transfer learning and GAN model

MM Mirimoghaddam, J Majidpour, F Pashaei… - Clinical Breast …, 2024 - Elsevier
Introduction Immunohistochemistry (IHC) is crucial for breast cancer diagnosis,
classification, and individualized treatment. IHC is used to measure the levels of expression …

Computational methods for breast cancer molecular profiling through routine histopathology: A review

S Kunhoth, SA Maadeed, Y Akbari… - arxiv preprint arxiv …, 2024 - arxiv.org
Precision medicine has become a central focus in breast cancer management, advancing
beyond conventional methods to deliver more precise and individualized therapies …