BACKGROUND: A significant number of individuals undergoing coronary computed tomography angiography (CCTA) for suspected (CAD) have nonobstructive or no CAD. There is a need for clinically proven models that can predict the pretest probability of sta...
Philosophical transactions. Series A, Mathematical, physical, and engineering sciences
Sep 25, 2025
This paper examines the current challenges in computed tomography (CT), with a critical exploration of existing methodologies from a mathematical perspective. Specifically, it aims to identify research directions to enhance image quality in low-dose,...
Disaster medicine and public health preparedness
Sep 25, 2025
OBJECTIVES: Remote injury assessment during natural disasters poses major challenges for healthcare providers due to the inaccessibility of disaster sites. This study aimed to explore the feasibility of using artificial intelligence (AI) techniques f...
To overcome the limitations of electroacoustic tomography (EAT) in clinical settings-particularly the artifacts and distortions caused by limited-angle data acquisition-and enable accurate, efficient visualization of electric field distributions for ...
Analytical methods : advancing methods and applications
Sep 25, 2025
Simultaneous monitoring of catecholamine neurotransmitters (CNTs)-including epinephrine (Epi), norepinephrine (NE), levodopa (L-DOPA), and dopamine (DA)-is essential for the accurate diagnosis and effective management of various neurological disorder...
. Biological signals can be used to record sleep activities and can be used to identify sleep disorders. Insomnia is a sleep disorder that can be detected using supervised learning models developed using biological signal analysis. The baseline insom...
The COVID-19 pandemic has demanded urgent and accelerated action toward developing effective therapeutic strategies. Drug repurposing models (in silico) are in high demand and require accurate and reliable molecular interaction data. While experiment...
This paper aims to measure credit risks of unlisted agricultural enterprises by using the KMV model integrating a CNN-BiLSTM neural network. Initially, the expected default frequencies (EDF) for each listed agricultural enterprise are computed using ...
In financial markets, predicting stock returns is an essential task for investors. This paper is one of the first studies using business efficiency scores calculated from data envelopment analysis to predict stock returns. In the meantime, this is al...
Household surveys have been the foundation for poverty measurement in developing countries for the past half-century, but the spatial and temporal gaps in these survey data often limit how well anti-poverty programs can be targeted, monitored, or eva...
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