Latest AI and machine learning research in pathology for healthcare professionals.
Histopathological diagnosis of cutaneous drug eruptions (CDEs) presents a challenge in dermatopathol...
The integration of multi-stain histopathology images through deep learning poses a significant chall...
Hepatocellular carcinoma is a leading cause of cancer mortality globally. Liver transplantation is c...
Accurate quantitative assessment of temporal bone microanatomy is essential for otologic research an...
PURPOSE: To develop and validate a multimodal deep learning framework that integrates clinical metad...
Data scarcity, inter-institutional stain variability, and privacy constraints are major challenges i...
BACKGROUND: Breast cancer (BRCA) is a heterogeneous disease. Accurate prognosis and molecular subtyp...
Cancers of unknown primary (CUP) refer to a highly heterogeneous group of metastatic tumors whose pr...
BACKGROUND: Real-time endoscopic diagnosis of Helicobacter pylori infection remains challenging and ...
OBJECTIVE: Based on multidimensional data analysis, potential biomarkers for ulcerative colitis were...
Conventional two-dimensional (2D) pathology relies on a limited number of tissue sections and theref...
OBJECTIVES: To investigate the performance of an artificial intelligence (AI) diagnostic system for ...
DNA-based molecular classifiers have emerged as a promising strategy for precise cancer diagnosis, o...
Deep learning can extract predictive and prognostic biomarkers from histopathology whole-slide image...
BACKGROUND: Obesity is the largest risk factor for endometrial cancer. Body Mass Index (BMI) does no...
Acute respiratory distress syndrome (ARDS) is associated with high mortality, and increasing evidenc...
Accurate estimation of spatially heterogeneous conductivity distributions is essential for reliable ...
BACKGROUND: Membranous nephropathy (MN) is an autoimmune disease characterized by immune complex dep...
INTRODUCTION: Although AI-powered digital morphology analyzers are widely used for leukocyte classif...
RATIONALE AND OBJECTIVES: To describe clinicopathologic and ultrasonographic heterogeneity across im...
BACKGROUND: To develop and validate a multimodal MRI radiomics machine learning model for differenti...