Latest AI and machine learning research in pathology for healthcare professionals.
Oral potentially malignant disorders (OPMDs) can directly progress to cancer, necessitating accurate...
INTRODUCTION: Type 2 diabetes (T2D) is a progressive metabolic disorder characterized by insulin res...
Increasing evidence suggests that disulfidptosis plays a crucial role in tumorigenesis and progressi...
Certain characteristics, such as high heterogeneity, a complex tumor microenvironment, metastatic po...
Gliomas are the most common type of primary brain tumors. Their management options and outcomes depe...
The widespread adoption of computed tomography has increased the detection of lung nodules. However,...
Accurate differentiation between benign and malignant thyroid nodules remains challenging in clinica...
Convolutional Neural Networks are widely used in lung cancer detection for more than a decade. Howev...
Exposure to perfluorooctanoic acid (PFOA) and perfluorooctane sulfonate (PFOS) has been associated w...
Programmed cell death (PCD) and cellular immunity play pivotal roles in colorectal cancer (CRC) prog...
Liquid biopsy via plasma cell-free DNA (cfDNA) is transforming precision medicine by enabling non-in...
BACKGROUND: The exact molecular mechanisms governing a heightened risk of chronic spontaneous urtica...
The 6th edition of the WHO Classification of Breast Tumours introduces both major and minor changes ...
The transformation of anatomic pathology from microscope-based practice to digital and computational...
OBJECTIVES: To characterize clinical-pathologic tumor features associated with artificial intelligen...
Insects comprise millions of species, many experiencing severe population declines under environment...
BACKGROUND: Oral squamous cell carcinoma (OSCC) remains a leading cause of cancer-related morbidity ...
OBJECTIVES: To validate blood oxygen level-dependent MRI (BOLD-MRI) for non-invasive discrimination ...
Intraoperative frozen section pathological diagnosis of lung adenocarcinoma serves as the gold stand...
We present a universal modular deep-learning framework and demonstrate its application to low-latenc...
BACKGROUND: Accurate prediction of clinical outcomes is challenging yet important for patient care. ...