A visual–language foundation model for pathology image analysis using medical twitter
The lack of annotated publicly available medical images is a major barrier for computational
research and education innovations. At the same time, many de-identified images and much …
research and education innovations. At the same time, many de-identified images and much …
A visual-language foundation model for computational pathology
The accelerated adoption of digital pathology and advances in deep learning have enabled
the development of robust models for various pathology tasks across a diverse array of …
the development of robust models for various pathology tasks across a diverse array of …
[HTML][HTML] Computational pathology: a survey review and the way forward
Abstract Computational Pathology (CPath) is an interdisciplinary science that augments
developments of computational approaches to analyze and model medical histopathology …
developments of computational approaches to analyze and model medical histopathology …
[HTML][HTML] Artificial intelligence in breast cancer diagnosis and personalized medicine
Breast cancer is a significant cause of cancer-related mortality in women worldwide. Early
and precise diagnosis is crucial, and clinical outcomes can be markedly enhanced. The rise …
and precise diagnosis is crucial, and clinical outcomes can be markedly enhanced. The rise …
A population-level digital histologic biomarker for enhanced prognosis of invasive breast cancer
Breast cancer is a heterogeneous disease with variable survival outcomes. Pathologists
grade the microscopic appearance of breast tissue using the Nottingham criteria, which are …
grade the microscopic appearance of breast tissue using the Nottingham criteria, which are …
AI-enabled routine H&E image based prognostic marker for early-stage luminal breast cancer
Breast cancer (BC) grade is a well-established subjective prognostic indicator of tumour
aggressiveness. Tumour heterogeneity and subjective assessment result in high degree of …
aggressiveness. Tumour heterogeneity and subjective assessment result in high degree of …
Co-pilot: Dynamic top-down point cloud with conditional neighborhood aggregation for multi-gigapixel histopathology image representation
Predicting survival rates based on multi-gigapixel histopathology images is one of the most
challenging tasks in digital pathology. Due to the computational complexities, Multiple …
challenging tasks in digital pathology. Due to the computational complexities, Multiple …
A foundational multimodal vision language AI assistant for human pathology
The field of computational pathology has witnessed remarkable progress in the
development of both task-specific predictive models and task-agnostic self-supervised vision …
development of both task-specific predictive models and task-agnostic self-supervised vision …
A whole-slide foundation model for digital pathology from real-world data
Digital pathology poses unique computational challenges, as a standard gigapixel slide may
comprise tens of thousands of image tiles,–. Prior models have often resorted to …
comprise tens of thousands of image tiles,–. Prior models have often resorted to …
Immune biomarkers in triple-negative breast cancer: improving the predictivity of current testing methods
Triple-negative breast cancer (TNBC) poses a significant challenge in terms of prognosis
and disease recurrence. The limited treatment options and the development of resistance to …
and disease recurrence. The limited treatment options and the development of resistance to …