Latest AI and machine learning research in radiology for healthcare professionals.
OBJECTIVES: The radiological imaging industry is developing and starting to offer a range of novel a...
Intracranial aneurysms (IAs) are a common vascular pathology and are associated with a risk of ruptu...
BACKGROUND: This study is to propose a clinically applicable 2-echelon (2e) diagnostic criteria for ...
Artificial intelligence (AI) has made significant advances in radiology. Nonetheless, challenges in ...
The aim of this paper was to explore the role of artificial intelligence (AI) applied to ultrasound ...
BACKGROUND: Positron emission tomography (PET) has been investigated for its ability to reconstruct ...
Brain atrophy measurements derived from magnetic resonance imaging (MRI) are a promising marker for ...
Deep neural networks have shown excellent performance in medical image segmentation, especially for ...
PURPOSE OF REVIEW: Pulmonary hypertension is a heterogeneous condition with significant morbidity an...
The radiological characterization of soil contaminated with natural radionuclides enables the classi...
PURPOSE: To develop a deep learning (DL) model for differentiating between benign and malignant ovar...
A three-dimensional convolutional neural network model was developed to classify the severity of chr...
Ultrasound elastography is a noninvasive medical imaging technique that maps viscoelastic properties...
PURPOSE: To validate the performance of a recently created risk stratification system (RSS) for thyr...
Pseudoprogression (PSP) is a related reaction of glioblastoma treatment, and misdiagnosis can lead t...
TumorPrism3D software was developed to segment brain tumors with a straightforward and user-friendly...
OBJECTIVE: Accurately predicting knee osteoarthritis (KOA) is essential for early detection and pers...
PURPOSE: This study was designed to develop and validate a machine learning-based, multimodality fus...
Screening mammography reduces breast cancer mortality, but studies analyzing interval cancers diagno...
PURPOSE: To evaluate lymphovascular invasion (LVI) in breast cancer by comparing the diagnostic perf...
Deep-learning tools that extract prognostic factors derived from multi-omics data have recently cont...