Latest AI and machine learning research in pathology for healthcare professionals.
Tire and Road Wear Particles (TRWP) are pervasive environmental contaminants, yet the molecular mech...
Plant pathogenic fungi severely threaten global agriculture, causing substantial yield losses in sta...
Prostate cancer (PCa) is among the most prevalent malignancies affecting men globally. The immunosup...
Thymic epithelial tumors (TETs), comprising thymomas, thymic carcinomas, and thymic neuroendocrine n...
Ultrasound radiomics is gradually emerging as a powerful tool for improving the diagnosis and manage...
Squamous cell carcinoma (SCC) is a common malignancy that arises in diverse organs and often exhibit...
OBJECTIVE: To support cancer screening and identify precancerous conditions, such as atypical hyperp...
A major challenge in deciphering the complex genetic landscape of polycystic ovary syndrome (PCOS) l...
BACKGROUND: Sampling techniques have poor accuracy for classifying biliary strictures as benign or m...
PURPOSE: An emerging application of artificial intelligence (AI) in cervical cytology is its use as ...
OBJECTIVES: Early vocal changes such as hoarseness or voice fatigue are common and often attributed ...
The tumor microenvironment (TME), composed of tumor cells together with stromal cells, immune cells,...
Intervertebral disc degeneration (IDD) is a prevalent disease with an increasing incidence, and agin...
Cystic breast lesions are commonly encountered on breast ultrasound, encompassing a spectrum from si...
BACKGROUND: Pathological scars, including hypertrophic scars and keloids, are fibrotic skin disorder...
Breast tumor is the most commonly detected tumors and remain one of the leading causes of cancer-rel...
Magnetic resonance imaging (MRI) is essential in the accurate diagnosis of brain tumors so that soun...
Social insect pollinators, such as bumblebees, face increasing threats from environmental agrochemic...
Surface-enhanced Raman scattering (SERS) nanoprobe-based immunoassay is an emerging liquid biopsy mo...
Achieving high spatial resolution is critical for revealing tissue-specific metabolite distributions...
Purpose To develop an explainable radio-pathomic graph deep-learning (RPGDL) system for multiscale s...