Multiple instance learning for digital pathology: A review of the state-of-the-art, limitations & future potential
M Gadermayr, M Tschuchnig - Computerized Medical Imaging and …, 2024 - Elsevier
Digital whole slides images contain an enormous amount of information providing a strong
motivation for the development of automated image analysis tools. Particularly deep neural …
motivation for the development of automated image analysis tools. Particularly deep neural …
One label is all you need: Interpretable AI-enhanced histopathology for oncology
Artificial Intelligence (AI)-enhanced histopathology presents unprecedented opportunities to
benefit oncology through interpretable methods that require only one overall label per …
benefit oncology through interpretable methods that require only one overall label per …
[HTML][HTML] Contrastive multiple instance learning: An unsupervised framework for learning slide-level representations of whole slide histopathology images without …
Simple Summary Recent AI methods in the automated analysis of histopathological imaging
data associated with cancer have trended towards less supervision by humans. Yet, there …
data associated with cancer have trended towards less supervision by humans. Yet, there …
Label-efficient deep learning in medical image analysis: Challenges and future directions
Deep learning has seen rapid growth in recent years and achieved state-of-the-art
performance in a wide range of applications. However, training models typically requires …
performance in a wide range of applications. However, training models typically requires …
[HTML][HTML] NRK-ABMIL: Subtle Metastatic Deposits Detection for Predicting Lymph Node Metastasis in Breast Cancer Whole-Slide Images
Simple Summary Recent advancements in AI have revolutionized cancer research,
especially in the analysis of histopathological imaging data with minimal human …
especially in the analysis of histopathological imaging data with minimal human …
[HTML][HTML] BCR-Net: A deep learning framework to predict breast cancer recurrence from histopathology images
Breast cancer is the most common malignancy in women, with over 40,000 deaths annually
in the United States alone. Clinicians often rely on the breast cancer recurrence score …
in the United States alone. Clinicians often rely on the breast cancer recurrence score …
[HTML][HTML] Bilateral adaptive graph convolutional network on CT based Covid-19 diagnosis with uncertainty-aware consensus-assisted multiple instance learning
Abstract Coronavirus disease (COVID-19) has caused a worldwide pandemic, putting
millions of people's health and lives in jeopardy. Detecting infected patients early on chest …
millions of people's health and lives in jeopardy. Detecting infected patients early on chest …
[HTML][HTML] Applications of discriminative and deep learning feature extraction methods for whole slide image analysis: A survey
Digital pathology technologies, including whole slide imaging (WSI), have significantly
improved modern clinical practices by facilitating storing, viewing, processing, and sharing …
improved modern clinical practices by facilitating storing, viewing, processing, and sharing …
Data efficient deep learning for medical image analysis: A survey
The rapid evolution of deep learning has significantly advanced the field of medical image
analysis. However, despite these achievements, the further enhancement of deep learning …
analysis. However, despite these achievements, the further enhancement of deep learning …
A Clinically Guided Graph Convolutional Network for Assessment of Parkinsonian Pronation-Supination Movements of Hands
In the clinically widely used rating scale (MDS-UPDRS), the pronation-supination movement
task of hands is required for assessment of bradykinesia, which is a typical clinical symptom …
task of hands is required for assessment of bradykinesia, which is a typical clinical symptom …