Background Cardiac arrhythmia is a cardiovascular disorder characterized by disturbances
in the heartbeat caused by electrical conduction anomalies in cardiac muscle. Clinically …

The rapid advancement of deep neural networks (DNNs) has significantly transformed
various sectors, demonstrating unparalleled proficiency in managing intricate tasks in …

To evaluate the health and well-being of an unborn child throughout pregnancy, fetal risk
prediction is a crucial component of prenatal care. The evaluation of potential risks and …

Early detection of adverse birth outcomes is vital as they are major contributors to neonatal
mortality and irreversible neurological complications in infants. These outcomes are typically …

The inherent variability in the visual interpretation of cardiotocograms (CTGs) by obstetric
clinical experts, both intra-and inter-observer, presents a substantial challenge in obstetric …

Cardiotocography (CTG) is a clinical procedure that is used to track and gauge the severity
of fetal distress. Although CTG is the most often used equipment to monitor and assess the …

Given the recent emergence of deep neural networks and their remarkable ability to handle
complex tasks across various “elds and modalities, it is expected that fetal monitoring …

Due to the variable working environment of bearings, the collected data often follow different
probability distributions. It is hard to directly use the trained models to identify the bearing …

Abstract Machine Learning (ML) relies on both data and algorithms for optimal functioning.
While conventional ML research often emphasizes algorithmic improvements, the …

This work compares the performance of different algorithms—Quantum Fourier Transform,
Gaussian-Newton Method, HyperFast, Metropolis-Adjusted Langevin Algorithm, and Non …