AIMC Topic: Pathology

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High-Order Correlation-Guided Slide-Level Histology Retrieval With Self-Supervised Hashing.

IEEE transactions on pattern analysis and machine intelligence
Histopathological Whole Slide Images (WSIs) play a crucial role in cancer diagnosis. It is of significant importance for pathologists to search for images sharing similar content with the query WSI, especially in the case-based diagnosis. While slide...

Proportionally Fair Hospital Collaborations in Federated Learning of Histopathology Images.

IEEE transactions on medical imaging
Medical centers and healthcare providers have concerns and hence restrictions around sharing data with external collaborators. Federated learning, as a privacy-preserving method, involves learning a site-independent model without having direct access...

How to use AI in pathology.

Genes, chromosomes & cancer
AI plays an important role in pathology, both in clinical practice supporting pathologists in their daily work, and in research discovering novel biomarkers for improved patient care. Still, AI is in its starting phase, and many pathology labs still ...

What Works Where and How for Uptake and Impact of Artificial Intelligence in Pathology: Review of Theories for a Realist Evaluation.

Journal of medical Internet research
BACKGROUND: There is increasing interest in the use of artificial intelligence (AI) in pathology to increase accuracy and efficiency. To date, studies of clinicians' perceptions of AI have found only moderate acceptability, suggesting the need for fu...

Predictive uncertainty estimation for out-of-distribution detection in digital pathology.

Medical image analysis
Machine learning model deployment in clinical practice demands real-time risk assessment to identify situations in which the model is uncertain. Once deployed, models should be accurate for classes seen during training while providing informative est...

Recommendations on compiling test datasets for evaluating artificial intelligence solutions in pathology.

Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc
Artificial intelligence (AI) solutions that automatically extract information from digital histology images have shown great promise for improving pathological diagnosis. Prior to routine use, it is important to evaluate their predictive performance ...

Non-invasive scoring of cellular atypia in keratinocyte cancers in 3D LC-OCT images using Deep Learning.

Scientific reports
Diagnosis based on histopathology for skin cancer detection is today's gold standard and relies on the presence or absence of biomarkers and cellular atypia. However it suffers drawbacks: it requires a strong expertise and is time-consuming. Moreover...

Digital pathology and artificial intelligence in translational medicine and clinical practice.

Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc
Traditional pathology approaches have played an integral role in the delivery of diagnosis, semi-quantitative or qualitative assessment of protein expression, and classification of disease. Technological advances and the increased focus on precision ...