Latest AI and machine learning research in pathology for healthcare professionals.
PURPOSE: A multimodal artificial intelligence (MMAI) biomarker was developed using clinical trial da...
BACKGROUND: Esophageal squamous cell carcinoma is a major histological subtype of esophageal cancer....
Single-molecule RNA imaging has been made possible with the recent advances in microscopy methods....
Recent advances in self-supervised deep learning have improved our ability to quantify cellular mo...
In modern society, Attention-Deficit/Hyperactivity Disorder (ADHD) is one of the common mental dis...
The diagnosis of pathological images is often limited by expert availability and regional disparit...
Medical image segmentation has achieved remarkable success through the continuous advancement of U...
The histopathological images contain a huge amount of information, which can make diagnosis an ext...
Gene expression profiling provides critical insights into cellular heterogeneity, biological proce...
Accurate and efficient cell detection is crucial in many biomedical image analysis tasks. We evalu...
Image segmentation is crucial in many computational pathology pipelines, including accurate diseas...
Lung cancer remains one of the leading causes of cancer-related mortality worldwide, with early an...
Radiologists routinely detect and size lesions in CT to stage cancer and assess tumor burden. To p...
DNA methylation is an epigenetic mechanism that regulates gene expression by adding methyl groups ...
Robust localization of lymph nodes (LNs) in multiparametric MRI (mpMRI) is critical for the assess...
BACKGROUND: Early detection of esophageal squamous neoplasms (ESN) is essential for improving patien...
In the field of deep learning, large architectures often obtain the best performance for many task...
Computational pathology, which involves analyzing whole slide images for automated cancer diagnosi...
Despite the impressive performance across a wide range of applications, current computational path...
Ultrasound is a widely accessible and cost-effective medical imaging tool commonly used for prenat...
We present a global explainability method to characterize sources of errors in the histology predi...