Latest AI and machine learning research in radiology for healthcare professionals.
BACKGROUND: Non-alcoholic fatty liver disease (NAFLD) is a significant risk factor for liver cancer ...
With the shift toward de-escalating surgery in breast cancer, prediction models incorporating imagin...
OBJECTIVES: Currently, radiomics focuses on intratumoral regions and fixed peritumoral regions, and ...
OBJECTIVES: Quantifying diagnostic image quality (IQ) is not straightforward but essential for optim...
Super-resolution imaging has emerged as a rapidly advancing field in diagnostic ultrasound. Ultrasou...
Multiple Sclerosis (MS) is a chronic autoimmune disease that primarily affects the central nervous s...
There is a pressing need for improved standardization of terminology and data in nuclear medicine. T...
In this study, we present enhanced physics-informed neural networks (PINNs), which were designed to ...
OBJECTIVES: To evaluate the diagnostic performance of multiparametric ultrasound (mpUS) and AI-assis...
Predicting the risk of breast cancer recurrence is crucial for guiding therapeutic strategies, inclu...
OBJECTIVE: As increased nuchal translucency (NT) thickness is notably associated with fetal chromoso...
Breast cancer is the leading cause of death among women worldwide, and early detection through the s...
. Artificial intelligence (AI) tools for evaluating low-dose CT (LDCT) lung cancer screening examina...
PURPOSE: To establish a predictive model for the sonication energy required for focused ultrasound s...
INTRODUCTION: Brucella spondylitis (BS) and tuberculous spondylitis (TS) are prevalent spinal infect...
BACKGROUND: In most medical centers, particularly in primary hospitals, non-contrast computed tomogr...
Diabetic retinopathy (DR) is an age-related macular degeneration eye disease problem that causes pat...
Magnetic resonance imaging of the lumbar spine is a key technique for clarifying the cause of diseas...
Dementia is a degenerative and chronic disorder, increasingly prevalent among older adults, posing s...
PURPOSE: To establish an interpretable and non-invasive machine learning (ML) model using clinicorad...
Purpose To improve the generalizability of pathologic complete response (pCR) prediction following ...