Latest AI and machine learning research in pathology for healthcare professionals.
BACKGROUND: This study aimed to develop and internally validate a machine learning-based model for predicting endometrial malignancy, defined as atypical hyperplasia or endometrial cancer (AH/EC), in postmenopausal women, integrating routinely available clinical, ultrasound, and laboratory features to support individualized diagnostic triage and potentially reduce unnecessary invasive diagnostic p...
BACKGROUND: R-loops regulate genome stability and transcription, but their roles in uveal melanoma (UVM) are unclear. METHODS: A total of 1,185 R-loop regulators were analyzed across TCGA-UVM and GEO cohorts. We utilized ssGSEA to assess global R-loop activity and conducted integrative bioinformatic screening to identify key regulators associated with poor prognosis and metastasis. The study focus...
BACKGROUND: While expression-based signatures inform adjuvant therapy in breast cancer (BC), no approved molecular biomarkers exist for the neoadjuvan...
Endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) is the standard minimally invasive modality for mediastinal staging in no...
BACKGROUND: Sentinel node biopsy (SNB) provides pathological staging of the neck in T1/T2 node-negative oral squamous cell carcinoma (OSCC). Up to 85%...
Artificial intelligence (AI) is increasingly applied to biomedical research, but most current systems remain limited to specific tasks, data types, or...
Hepatocellular carcinoma (HCC) is a leading cause of cancer-related mortality. Machine learning (ML) may enable the noninvasive prediction of histopat...
Early liver metastasis is a major factor contributing to the poor prognosis of pancreatic ductal adenocarcinoma (PDAC). Single-cell RNA sequencing (sc...
Dioxins are persistent environmental pollutants and key components of the human exposome with established carcinogenic potential. As airborne toxicant...
Prostate cancer (PCa) is the second most common malignancy in men worldwide, with rising mortality linked to late-stage diagnoses. While current diagn...
INTRODUCTION: To compare the diagnostic performance of endoscopy-based deep learning (DL) algorithms with endoscopists of different experience levels ...
Determining protein binding is fundamental to deciphering biochemical mechanisms and engineering advanced biosensors, yet label-free imaging of single...
Neurodisorders pose a considerable burden to global health, frequently requiring early treatment and diagnosis to avoid irreversible cognitive and mot...
Adverse events (AEs) of small molecule kinase inhibitors (SMKIs) at therapeutic doses in cancer patients are largely unpredictable in phase I-III stud...
BACKGROUND: Non-invasive biomarkers offer potential to improve risk stratification and early diagnosis of lung cancer, complementing low-dose computed...
INTRODUCTION: Readily available predictive biomarkers for immune checkpoint inhibitor (ICI) response in advanced melanoma are limited. This study eval...
BACKGROUND: Colorectal cancer (CRC) is a leading cause of mortality worldwide, and early examination via colonoscopy is increasingly used to prevent C...
Pathologists diagnose and grade prostate cancer using thin two-dimensional (2D) histological sections, but these 3-5 micron sections are too thin to v...
PURPOSE: This study aims to facilitate virtual multiplexing by establishing a deep learning-based analytical framework for precise identification and ...
Mass spectrometry imaging (MSI) has emerged as a transformative technology in pharmaceutical research, offering unprecedented capabilities to visualiz...