We introduce a pioneering approach that integrates pathology imaging with transcriptomics and proteomics to identify predictive histology features associated with critical clinical outcomes in cancer. We utilize 2,755 H&E-stained histopathological sl...
Computational pathology refers to applying deep learning techniques and algorithms to analyse and interpret histopathology images. Advances in artificial intelligence (AI) have led to an explosion in innovation in computational pathology, ranging fro...
Computer methods and programs in biomedicine
Aug 9, 2023
BACKGROUND AND OBJECTIVE: Cancer grading in pathology image analysis is a major task due to its importance in patient care, treatment, and management. The recent developments in artificial neural networks for computational pathology have demonstrated...
IEEE transactions on pattern analysis and machine intelligence
Aug 7, 2023
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...
Clinical efforts on precision medicine are driving the need for accurate diagnostic, new prognostic and novel drug predictive assays to inform patient selection and stratification for disease treatment. Accumulating evidence suggests that a combinati...
The detection of somatic DNA variants in tumor samples with low tumor purity or sequencing depth remains a daunting challenge despite numerous attempts to address this problem. In this study, we constructed a substantially extended set of actual posi...