Latest AI and machine learning research in pathology for healthcare professionals.
The kidney allograft has been under continuous attack from diverse injuries since the very beginning of organ procurement, leading to a gradual decline in function, chronic fibrosis, and allograft loss. It is vital to routinely and precisely monitor the risk of injuries after renal transplantation, which is difficult to achieve because the traditional laboratory tests lack sensitivity and specific...
Ultrasound localization microscopy (ULM) enables deep tissue microvascular imaging by localizing and tracking intravenously injected microbubbles circulating in the bloodstream. However, conventional localization techniques require spatially isolated microbubbles, resulting in prolonged imaging time to obtain detailed microvascular maps. Here, we introduce LOcalization with Context Awareness (LOCA...
Assessing programmed death ligand 1 (PD-L1) expression on tumor cells (TCs) using Food and Drug Administration-approved, validated immunoassays can gu...
Peripheral artery disease (PAD) is associated with impaired blood flow in the lower extremities and histopathologic changes of the skeletal calf muscl...
Variations in color and texture of histopathology images are caused by differences in staining conditions and imaging devices between hospitals. These...
Thyroid nodules are a common occurrence, and although most are non-cancerous, some can be malignant. The American College of Radiology has developed t...
Digitization of pathological slides has promoted the research of computer-aided diagnosis, in which artificial intelligence analysis of pathological i...
INTRODUCTION: Malignant cerebral edema (MCE) is a serious complication and the main cause of poor prognosis in patients with large-hemisphere infarcti...
AIMS: Deep learning holds immense potential for histopathology, automating tasks that are simple for expert pathologists and revealing novel biology f...
Breast cancer is a major health threat, with early detection crucial for improving cure and survival rates. Current systems rely on imaging technology...
An intraoperative diagnosis is critical for precise cancer surgery. However, traditional intraoperative assessments based on hematoxylin and eosin (H&...
BACKGROUND: Histopathology remains the gold standard for diagnosing and staging metabolic dysfunction-associated steatotic liver disease (MASLD). The ...
Light-sheet microscopy has made possible the 3D imaging of both fixed and live biological tissue, with samples as large as the entire mouse brain. How...
Accurate placenta pathology assessment is essential for managing maternal and newborn health, but the placenta's heterogeneity and temporal variabilit...
PURPOSE: To distinguish malignant and benign bowel wall thickening (BWT) by using computed tomography (CT) texture features based on machine learning ...
Analysis of the mechanisms underlying the occurrence and progression of cancer represents a key objective in contemporary clinical bioinformatics and ...
Valvular heart disease (VHD) is becoming more prevalent in an ageing population, leading to challenges in diagnosis and management. This two-part Seri...
Deep learning methods have emerged as powerful tools for analyzing histopathological images, but current methods are often specialized for specific do...
Histopathology and genomic profiling are cornerstones of precision oncology and are routinely obtained for patients with cancer. Traditionally, histop...
Proteins need to be located in appropriate spatiotemporal contexts to carry out their diverse biological functions. Mislocalized proteins may lead to ...