Latest AI and machine learning research in pathology for healthcare professionals.
CONTEXT.—: Advances in computer vision have fueled the development of artificial intelligence (AI)-based algorithms for pathology. AI-assisted approaches may streamline the diagnostic workflow and reduce variability. OBJECTIVE.—: To assess the impact of an AI-assist model for human epidermal growth factor receptor 2 (HER2) scoring on pathologist reproducibility and accuracy and to understand patho...
Focused ultrasound (FUS) is an emerging therapeutic and diagnostic technology in neuro-oncology, offering new strategies for molecular diagnosis, drug delivery, and tumor ablation across a range of brain tumors, including glioblastoma (GBM), brain metastases, and diffuse intrinsic pontine glioma (DIPG). The prognosis for aggressive brain tumors remains poor, despite advances in surgery, radiation,...
Extracellular vesicles (EVs) have emerged as promising biomarkers for liquid biopsy. However, their clinical detection is hampered by heterogeneity an...
Analysis of tumors using single-cell and spatial modalities is critical to advance our understanding of cancer. The growth of technologies that enable...
BACKGROUND: Urogenital schistosomiasis caused by Schistosoma haematobium remains endemic in sub-Saharan Africa. Diagnosis traditionally relies on urin...
Hirschsprung disease (HD) is a congenital disorder characterized by the absence of ganglion cells in the colonic nervous plexuses, resulting in bowel ...
Breast cancer is a leading cause of mortality among women globally, highlighting the need for accurate and robust diagnostic systems. This study prese...
BACKGROUND: Artificial intelligence has significantly advanced computational pathology by enabling high-resolution, clinical-grade tumor segmentation ...
Manual detection of breast cancer in histopathology images is a highly complex task due to variations in tissue appearance and the requirement for ana...
Vision Transformers (ViTs) are one of the powerful tools in medical imaging, providing new possibilities for pancreatic cancer diagnosis. In recent ye...
Fluorescence microscopy is constrained by optical limits, fluorophore chemistry and finite photon budgets, imposing trade-offs between imaging speed, ...
Deep learning (DL) systems could improve diagnostic accuracy and efficiency in detecting cervical atypia, but their effectiveness remains insufficient...
BACKGROUND AND OBJECTIVE: Colon cancer (CC) is a highly prevalent malignant tumor with a high mortality rate worldwide. Despite recent advancements in...
Accurate prediction of a compound's site(s) of metabolism (SoMs) mediated by cytochromes P450 (CYP450) is advantageous in the early stage of drug disc...
Neutrophil extracellular traps (NETs) are increasingly recognized as critical mediators in vascular inflammation and remodeling, yet their molecular m...
Spatial transcriptomics (ST) technologies have transformed our ability to examine gene expression within intact tissues, yet accurately identifying sp...
PURPOSE: Quantifying collagen in histological slides is essential for diagnosing and monitoring fibrosis. However, the combination of PicroSirius Red ...
The global demographic shift toward aging has precipitated a surge in age-related ocular pathologies, imposing a formidable public health challenge th...
Molecular subtyping is essential for guiding systemic therapy in breast cancer but currently requires invasive biopsy. Conventional B-mode ultrasound ...
AIM: To develop and validate a deep learning-based AI system for the dynamic, real-time differentiation of benign and malignant gastric ulcers during ...