From whole-slide image to biomarker prediction: end-to-end weakly supervised deep learning in computational pathology
Hematoxylin-and eosin-stained whole-slide images (WSIs) are the foundation of diagnosis
of cancer. In recent years, development of deep learning-based methods in computational …
of cancer. In recent years, development of deep learning-based methods in computational …
Characterising reproducibility debt in scientific software: A systematic literature review
Context: In scientific software, the inability to reproduce results is often due to technical
issues and challenges in recreating the full computational workflow from the original …
issues and challenges in recreating the full computational workflow from the original …
Open and reusable deep learning for pathology with WSInfer and QuPath
Digital pathology has seen a proliferation of deep learning models in recent years, but many
models are not readily reusable. To address this challenge, we developed WSInfer: an open …
models are not readily reusable. To address this challenge, we developed WSInfer: an open …
ConvNext Mitosis Identification—You Only Look Once (CNMI-YOLO): Domain Adaptive and Robust Mitosis Identification in Digital Pathology
In digital pathology, accurate mitosis detection in histopathological images is critical for
cancer diagnosis and prognosis. However, this remains challenging due to the inherent …
cancer diagnosis and prognosis. However, this remains challenging due to the inherent …
[HTML][HTML] Weakly Supervised Multiple Instance Learning Model With Generalization Ability for Clinical Adenocarcinoma Screening on Serous Cavity Effusion Pathology
Y Zhang, X Zhu, L Zhong, J Wu, J Chen, H Yang… - Modern Pathology, 2025 - Elsevier
Accurate and rapid screening of adenocarcinoma cells in serous cavity effusion is vital in
diagnosing the stage of metastatic tumors and providing prompt medical treatment …
diagnosing the stage of metastatic tumors and providing prompt medical treatment …
[HTML][HTML] Synergies and Challenges in the Preclinical and Clinical Implementation of Pathology Artificial Intelligence Applications
Recent introduction of digitalization in pathology has disrupted the field greatly with the
potential to change the area immensely. Digital pathology has created the potential of …
potential to change the area immensely. Digital pathology has created the potential of …
The Quest for the Application of Artificial Intelligence to Whole Slide Imaging: Unique Prospective from New Advanced Tools
The introduction of machine learning in digital pathology has deeply impacted the field,
especially with the advent of whole slide image (WSI) analysis. In this review, we tried to …
especially with the advent of whole slide image (WSI) analysis. In this review, we tried to …
An AI based, open access screening tool for early diagnosis of Burkitt lymphoma
N Nambiar, V Rajesh, A Nair, S Nambiar, R Nair… - Frontiers in …, 2024 - frontiersin.org
Burkitt Lymphoma (BL) is a highly treatable cancer. However, delayed diagnosis of BL
contributes to high mortality in BL endemic regions of Africa. Lack of enough pathologists in …
contributes to high mortality in BL endemic regions of Africa. Lack of enough pathologists in …
[HTML][HTML] HcGAN: Harmonic conditional generative adversarial network for efficiently generating high-quality IHC images from H&E
S Wu, S Xu - Heliyon, 2024 - cell.com
Generating high quality histopathology images like immunohistochemistry (IHC) stained
images is essential for precise diagnosis and the advancement of computer-aided …
images is essential for precise diagnosis and the advancement of computer-aided …
Reproducibility and explainability in digital pathology: The need to make black-box artificial intelligence systems more transparent
Artificial intelligence (AI), and more specifically Machine Learning (ML) and Deep learning
(DL), has permeated the digital pathology field in recent years, with many algorithms …
(DL), has permeated the digital pathology field in recent years, with many algorithms …