3D conventional photoacoustic (PA) imaging often suffers from visibility artifacts caused by the limited bandwidth and constrained viewing angles of ultrasound transducers, as well as the use of sparse arrays. PA fluctuation imaging (PAFI), which lev...
Rapid and accurate quantitative assessment of muscle tissue characteristics is valuable for the diagnosis and monitoring of neuromuscular diseases (NMDs). Quantitative magnetic resonance imaging (MRI) enables non-invasive assessment of muscle patholo...
BACKGROUND: Previous studies have demonstrated that the triglyceride-glucose (TyG) index in combination with the estimated glucose disposal rate (eGDR) could predict mortality risks in the normal population. Our studies have focused on their additive...
Having an accurate reaction coordinate (RC) is essential for reliable kinetic characterization of molecular processes, but there are few quantitative metrics to evaluate RC quality. In this study, we consider the dimensionless γ metric from the Expon...
BACKGROUND: Deep learning (DL) models can quantify coronary artery calcification using non-gated chest CT scans. However, the prognostic value of a DL-based coronary artery calcium score (DL-CACS) for predicting major adverse cardiovascular events (M...
Regime switching in a time series is an important and challenging issue in complex financial system analysis. Existing regime models have focused on the features of fluctuations at a single point in financial time series, often neglecting time series...
Pharmacokinetic (PK) parameters derived from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) provide quantitative characterization of tissue perfusion and permeability. However, existing deep learning methods for PK parameter estimatio...
BACKGROUND: Patients with diabetes admitted to emergency care face a higher risk of complications, including prolonged hospital stays, admissions to the intensive care unit and mortality.
BACKGROUND: Early mortality prediction in critically ill patients with cardiovascular disease remains challenging. This study aimed to develop and validate an ensemble machine learning (ML) model to predict 30-day mortality, comparing its performance...
The ProVision scanner is a dedicated prostate positron emission tomography (PET) system with limited angular coverage; it employs a new detector technology that provides high spatial resolution as well as information about depth-of-interaction (DOI) ...
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