Latest AI and machine learning research in pathology for healthcare professionals.
Chronic rhinosinusitis with nasal polyps (CRSwNP) is characterized by inflammatory heterogeneity, epithelial hyperplasia, and tissue remodeling, with spatial pathology critical for deciphering pathological mechanisms and guiding clinical practice. Conventional histopathological techniques rely on subjective visual evaluation, limited by inadequate spatial resolution of molecular markers and imprec...
Borderline ovarian tumors (BOTs) are a distinct subgroup of epithelial ovarian neoplasms that commonly affect women of reproductive age and are associated with excellent overall survival. Management is primarily surgical and requires balancing oncologic considerations with fertility preservation. This narrative review summarizes current evidence regarding pathology, molecular features, surgical ma...
Primary cutaneous lymphomas (CL) and lymphoproliferative disorders (LPD) are heterogeneous T- and B-cell neoplasms defined by integrated clinical, his...
Deep learning models in computational pathology often fail to generalize across cohorts and institutions due to domain shift. Existing approaches eith...
Two-photon autofluorescence (TPAF) microscopy is a promising modality for rapid, label-free assessment of unstained tissue, but is fundamentally limit...
BACKGROUND: Lung neuroendocrine tumours (NETs, also known as carcinoids) are rapidly rising in incidence worldwide but have unknown aetiology and limi...
BACKGROUND: Detection of occult cervical lymph node metastases is critical for accurate staging and treatment planning in oral cavity squamous cell ca...
BACKGROUND AND AIMS: Pancreatic ductal adenocarcinoma (PDAC) remains one of the most lethal malignancies worldwide because most patients are diagnosed...
BACKGROUND: Recent genetic data suggest hereditary haemorrhagic telangiectasia (HHT) is 2-12 times more common than the clinically-ascertained prevale...
OBJECTIVES: The research question was: How accurate is artificial intelligence (AI) in diagnosing Oral Potentially Malignant Disorders (OPMD)/oral can...
BACKGROUND: Although large language models (LLMs) have demonstrated the ability to generate the impression section from radiology findings automatical...
MOTIVATION: Spatial transcriptomics (ST) technologies provide spatially resolved gene expression along with image data, allowing the integrative analy...
Fluorescence Molecular Tomography is a promising technique for non-invasive 3D visualization of fluorescent probes, but its reconstruction remains cha...
Metabolic dysfunction-associated steatotic liver disease (MASLD) is among the most prevalent chronic liver diseases worldwide. B-mode ultrasound remai...
Cancer diagnosis continues to rely on invasive tissue sampling and static molecular assessments that cannot reflect the real time RNA alterations driv...
Learning integrated representations from spatial multiomics data is a fundamental challenge, particularly in the context of diagonal integration, wher...
BACKGROUND: Accurate preoperative glioma grading and molecular subtyping are important for treatment. The vascular microenvironment promotes tumor pro...
Gastrointestinal endoscopy generates extensive high-resolution video data, posing significant challenges for efficient and accurate computer-aided dia...
Non-invasive follicular thyroid neoplasm with papillary-like nuclear features (NIFTP) and invasive encapsulated follicular variant of papillary thyroi...
Herbarium specimens are physical, verifiable records that form the basis of taxonomic knowledge and biodiversity research. Their large-scale digitizat...