PURPOSE: To evaluate the impact of deep learning-based post-hoc noise reduction (DLNR) on image quality, coronary artery disease reporting and data system (CAD-RADS) assessment, and diagnostic performance in quarter-dose versus full-dose coronary CT ...
RATIONALE AND OBJECTIVES: Timely and accurate classification of bacterial pneumonia (BP) is essential for guiding antibiotic therapy. However, distinguishing BP from non-bacterial pneumonia (NBP) using computed tomography (CT) is challenging due to o...
BACKGROUND: This study developed an explainable machine learning model for baseline internal mammary lymph node metastasis (IMNM) in breast cancer patients.
BACKGROUND: Early diagnosis of low ejection fraction (EF) remains challenging despite being a treatable condition. This study aimed to evaluate the effectiveness of an electrocardiogram (ECG)-based artificial intelligence (AI)-assisted clinical decis...
Machine learning (ML) classification of myocardial scarring in cardiac MRI is often hindered by limited explainability, particularly with convolutional neural networks (CNNs). To address this, we developed One Match (OM), an algorithm that builds on ...
Stroke is the second leading cause of death, accounting for 11% of deaths worldwide. Comparing diffusion-weighted imaging (DWI) and apparent diffusion coefficient (ADC) images is important for stroke diagnosis, but most studies have focused on lesion...
OBJECTIVES: To evaluate the diagnostic performance of lumbar spine CT using deep learning denoising (DLD CT) for detecting disc herniation and spinal stenosis.
OBJECTIVES: This study compared two uncertainty quantification (UQ) metrics to rule out prostate MRI scans with a high-confidence artificial intelligence (AI) prediction and investigated the resulting potential radiologist's workload reduction in a c...
International journal of medical informatics
Jun 7, 2025
BACKGROUND: Transcatheter heart valve (THV) durability is a critical concern, and its deformation may influence long-term performance. Current assessments rely on CT-based single-phase measurements and require a tedious analysis process, potentially ...
BACKGROUND AND OBJECTIVE: Telephone cancer information and support services (CISS) deliver essential evidence-based resources for people living with cancer. This research aimed to describe how attributes and levels were developed for a future discret...
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