Time for a full digital approach in nephropathology: a systematic review of current artificial intelligence applications and future directions
G Cazzaniga, M Rossi, A Eccher, I Girolami… - Journal of …, 2024 - Springer
Introduction Artificial intelligence (AI) integration in nephropathology has been growing
rapidly in recent years, facing several challenges including the wide range of histological …
rapidly in recent years, facing several challenges including the wide range of histological …
A CAD system for automatic dysplasia grading on H&E cervical whole-slide images
Cervical cancer is the fourth most common female cancer worldwide and the fourth leading
cause of cancer-related death in women. Nonetheless, it is also among the most …
cause of cancer-related death in women. Nonetheless, it is also among the most …
Image-Based Lung Analysis in the Context of Digital Pathology: A Brief Review
S Shahrabadi, J Carias, E Peres, LG Magalhães… - Procedia Computer …, 2024 - Elsevier
Lung cancer is the 2 nd most diagnosed cancer worldwide. The corresponding
histopathological analysis, being both costly and time-consuming, demands the commitment …
histopathological analysis, being both costly and time-consuming, demands the commitment …
[HTML][HTML] Majority voting of doctors improves appropriateness of AI reliance in pathology
Abstract As Artificial Intelligence (AI) making advancements in medical decision-making,
there is a growing need to ensure doctors develop appropriate reliance on AI to avoid …
there is a growing need to ensure doctors develop appropriate reliance on AI to avoid …
[HTML][HTML] SlideTiler: A dataset creator software for boosting deep learning on histological whole slide images
The introduction of deep learning caused a significant breakthrough in digital pathology.
Thanks to its capability of mining hidden data patterns in digitised histological slides to …
Thanks to its capability of mining hidden data patterns in digitised histological slides to …
A Survey on Cell Nuclei Instance Segmentation and Classification: Leveraging Context and Attention
Manually annotating nuclei from the gigapixel Hematoxylin and Eosin (H&E)-stained Whole
Slide Images (WSIs) is a laborious and costly task, meaning automated algorithms for cell …
Slide Images (WSIs) is a laborious and costly task, meaning automated algorithms for cell …
Deep Learning-based Prediction of Breast Cancer Tumor and Immune Phenotypes from Histopathology
T Gonçalves, D Pulido-Arias, J Willett… - arXiv preprint arXiv …, 2024 - arxiv.org
The interactions between tumor cells and the tumor microenvironment (TME) dictate
therapeutic efficacy of radiation and many systemic therapies in breast cancer. However, to …
therapeutic efficacy of radiation and many systemic therapies in breast cancer. However, to …
Supporting Mitosis Detection AI Training with Inter-Observer Eye-Gaze Consistencies
The expansion of artificial intelligence (AI) in pathology tasks has intensified the demand for
doctors' annotations in AI development. However, collecting high-quality annotations from …
doctors' annotations in AI development. However, collecting high-quality annotations from …
Enhancing AI Research for Breast Cancer: A Comprehensive Review of Tumor-Infiltrating Lymphocyte Datasets
The field of immunology is fundamental to our understanding of the intricate dynamics of the
tumor microenvironment. In particular, tumor-infiltrating lymphocyte (TIL) assessment …
tumor microenvironment. In particular, tumor-infiltrating lymphocyte (TIL) assessment …
Predicting DNA Content Abnormalities in Barrett's Esophagus: A Weakly Supervised Learning Paradigm
Barrett's esophagus (BE) is the sole precursor to esophageal adenocarcinoma (EAC), and is
an opportunity for developing biomarkers for cancer risk assessment. DNA content …
an opportunity for developing biomarkers for cancer risk assessment. DNA content …