[HTML][HTML] 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 …
[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 …
From whole-slide image to biomarker prediction: a protocol for end-to-end deep learning in computational pathology
OSM El Nahhas, M van Treeck, G Wölflein… - arXiv preprint arXiv …, 2023 - arxiv.org
Hematoxylin-and eosin (H&E) stained whole-slide images (WSIs) are the foundation of
diagnosis of cancer. In recent years, development of deep learning-based methods in …
diagnosis of cancer. In recent years, development of deep learning-based methods in …
[HTML][HTML] 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 …
Closing the gap in the clinical adoption of computational pathology: a standardized, open-source framework to integrate deep-learning algorithms into the laboratory …
M Angeloni, D Rizzi, S Schoen, A Caputo, F Merolla… - bioRxiv, 2024 - biorxiv.org
Digital pathology (DP) has revolutionized cancer diagnostics, allowing the development of
deep-learning (DL) models supporting pathologists in their daily work and contributing to the …
deep-learning (DL) models supporting pathologists in their daily work and contributing to the …
IHCScoreGAN: An unsupervised generative adversarial network for end-to-end ki67 scoring for clinical breast cancer diagnosis
C Molnar, TE Tavolara, CA Garcia… - Medical Imaging with … - openreview.net
Ki67 is a biomarker whose activity is routinely measured and scored by pathologists through
immunohistochemistry (IHC) staining, which informs clinicians of patient prognosis and …
immunohistochemistry (IHC) staining, which informs clinicians of patient prognosis and …
Characterising Reproducibility Debt in Scientific Software: A Systematic Literature Review
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 analysis. We …
challenges in recreating the full computational workflow from the original analysis. We …