Latest AI and machine learning research in pathology for healthcare professionals.
Hepatocellular carcinoma is a leading cause of cancer mortality globally. Liver transplantation is considered the best curative treatment for selected patients, as it removes the tumor and restores hepatic function. However, organ scarcity requires precise prognostic stratification. Histopathology is the essential bridge between morphology and biology, offering unique insights into tumor aggressiv...
Accurate quantitative assessment of temporal bone microanatomy is essential for otologic research and surgical planning. However, existing measurement approaches, including manual tools, ex vivo microscopy, and high-resolution computed tomography, are limited by contact requirements, indirect measurement, insufficient spatial resolution, or the inability to provide efficient quantitative feedback ...
PURPOSE: To develop and validate a multimodal deep learning framework that integrates clinical metadata with [18F]FDG PET/CT imaging to resolve overla...
Data scarcity, inter-institutional stain variability, and privacy constraints are major challenges impeding the development of generalizable artificia...
BACKGROUND: Breast cancer (BRCA) is a heterogeneous disease. Accurate prognosis and molecular subtypes are critical for personalized treatment in BRCA...
Cancers of unknown primary (CUP) refer to a highly heterogeneous group of metastatic tumors whose primary site remains undetectable despite comprehens...
BACKGROUND: Real-time endoscopic diagnosis of Helicobacter pylori infection remains challenging and often requires biopsy-based testing, delaying trea...
OBJECTIVE: Based on multidimensional data analysis, potential biomarkers for ulcerative colitis were screened, and the effects of curcumin chitosan mi...
PURPOSE: The aim of this study is to develop a deep learning model using preoperative multimodal MR data to predict the Ki-67 expression level of glio...
Conventional two-dimensional (2D) pathology relies on a limited number of tissue sections and therefore provides information from isolated planes, whi...
OBJECTIVES: To investigate the performance of an artificial intelligence (AI) diagnostic system for thyroid nodule sonography based on deep learning c...
DNA-based molecular classifiers have emerged as a promising strategy for precise cancer diagnosis, offering a superior alternative to invasive biopsy ...
Deep learning can extract predictive and prognostic biomarkers from histopathology whole-slide images. However, explainable artificial intelligence ap...
BACKGROUND: Obesity is the largest risk factor for endometrial cancer. Body Mass Index (BMI) does not fully capture obesity's metabolic and inflammato...
Acute respiratory distress syndrome (ARDS) is associated with high mortality, and increasing evidence suggests that air pollution may contribute to it...
Accurate estimation of spatially heterogeneous conductivity distributions is essential for reliable electric field modeling in non-invasive brain stim...
Spinal cord injury (SCI) is a highly disabling central nervous system disease with complex pathology, and targeted neuroprotective drugs remain clinic...
BACKGROUND: Membranous nephropathy (MN) is an autoimmune disease characterized by immune complex deposition and progressive renal function impairment....
INTRODUCTION: Although AI-powered digital morphology analyzers are widely used for leukocyte classification, their reliability in detecting clinically...
RATIONALE AND OBJECTIVES: To describe clinicopathologic and ultrasonographic heterogeneity across immunohistochemistry-based FUSCC surrogate subtypes ...