Latest AI and machine learning research in pathology for healthcare professionals.
Coronary microvascular dysfunction (CMD) affects millions worldwide yet remains underdiagnosed becau...
Deep learning models in computational pathology often fail to generalize across cohorts and institut...
Cervical intraepithelial neoplasia grade 2 (CIN2) lesions show variable outcomes, and accurate predi...
The last decade has seen significant advances in computer-aided diagnostics for cytological screenin...
Virtual immunohistochemistry (IHC) aims to computationally synthesize molecular staining patterns fr...
Early achievement of deep remission improves patients' outcome in chronic myeloid leukemia (CML) tre...
Somatic mutational signatures imprint the history of exogenous exposures and endogenous processes on...
Whole-brain simulations are a valuable tool for gaining insight into the multiscale processes that r...
Supervised deep learning models often achieve excellent performance within their training distributi...
Interpretability is significant in computational pathology, leading to the development of multimodal...
Microtubules are cytoskeletal filaments that play essential roles in many cellular processes and are...
Background: Live-cell fluorescence microscopy enables the study of dynamic cellular processes. Howev...
Understanding the role of tertiary lymphoid structures (TLS) is crucial in non-small cell lung cance...
Deep learning for cancer histopathology training conflicts with privacy constraints in clinical sett...
Spatial transcriptomics (ST) enables transcriptome-wide profiling while preserving the spatial conte...
Digital pathology plays a vital role across modern medicine, offering critical insights for disease ...
Breast cancer is one of the most common cancers among women worldwide, and its accurate and timely d...
The functions of different regions of the human brain are closely linked to their distinct cytoarchi...
Recent developments in spatial omics technologies have enabled the generation of high dimensional mo...
Foundation models have transformed medical image analysis by providing robust feature representation...
Medical Vision-language models (VLMs) have shown remarkable performances in various medical imaging ...