Latest AI and machine learning research in pathology for healthcare professionals.
Stain variability is a pervasive source of distribution shift and potential shortcut learning in ren...
Immunohistochemistry (IHC) is essential for assessing specific immune biomarkers like Human Epiderma...
Topological Data Analysis (TDA) provides tools to describe the shape of data, but integrating topolo...
We propose a geometric framework for longitudinal multi-parametric MRI analysis based on patient-spe...
Multiple Instance Learning (MIL) is the dominant framework for gigapixel whole-slide image (WSI) cla...
Automatic diagnosis of canine pneumothorax is challenged by data scarcity and the need for trustwort...
Scanning Electron Microscopy (SEM) is indispensable in modern materials science, enabling high-resol...
Collagen organisation within the tumour microenvironment plays a critical role in tumour progression...
Diffusion and flow-based generative models have shown strong potential for image restoration. Howeve...
Volumetric CT imaging is essential for clinical diagnosis, yet annotating 3D volumes is expensive an...
Breast cancer is a highly heterogeneous disease with diverse molecular profiles. The PAM50 gene sign...
Recent Text-to-Image (T2I) models based on rectified-flow transformers (e.g., SD3, FLUX) achieve hig...
Automated analysis of Pap smear images is critical for cervical cancer screening but remains challen...
Controlling the behavior of text-to-image generative models is critical for safe and practical deplo...
Introduction: Podocyte injury is central to the pathogenesis of most glomerulonephritides (GN) and c...
Generating realistic single-cell transcriptomic profiles from structured biological descriptions wou...
Nuclei instance segmentation is critical in computational pathology for cancer diagnosis and prognos...
Background Narcolepsy is a rare, lifelong neurological disorder that often begins in childhood or ad...
BACKGROUND: There is increasing momentum behind the clinical implementation of AI-based software for...
This study assesses whether self-supervised learning (SSL) improves knee osteoarthritis (OA) modelin...
Despite their great success, deep neural networks rely on high-dimensional, non-robust representatio...