Related papers: A machine learning method correlating pulse pressu…
Aortic valve stenosis (AVS) presents challenges in asymptomatic detection, resulting in delayed intervention. This study aims to understand how AVS affects pulse wave (PW) morphology. A PW database of 16,038 virtual subjects aged 50 to 75…
Parkinson's disease (PD) is a neuro-degenerative disorder that affects movement, speech, and coordination. Timely diagnosis and treatment can improve the quality of life for PD patients. However, access to clinical diagnosis is limited in…
Precision timing of highly stable milli-second pulsars is a promising technique for the detection of very low frequency sources of gravitational waves. In any single pulsar, a stochastic gravitational wave signal appears as an additional…
Myocardial infarction (MI), commonly known as a heart attack, is a critical health condition caused by restricted blood flow to the heart. Early-stage detection through continuous ECG monitoring is essential to minimize irreversible damage.…
Extensive research has been performed on continuous, non-invasive, cuffless blood pressure (BP) measurement using artificial intelligence algorithms. This approach involves extracting certain features from physiological signals like ECG,…
Early diagnosis and intervention are clinically considered the paramount part of treating cerebral palsy (CP), so it is essential to design an efficient and interpretable automatic prediction system for CP. We highlight a significant…
Pulsar timing, i.e. the analysis of the arrival times of pulses from a pulsar, is a powerful tool in modern astrophysics. It allows us to measure the time delays of an electromagnetic signal caused by a number of physical processes as the…
Utilizing mobile phone cameras for continuous blood pressure (BP) monitoring presents a cost-effective and accessible approach, yet it is challenged by limitations in accuracy and interpretability. This study introduces four innovative…
Parkinson's Disease (PD) is a chronic, degenerative disorder which leads to a range of motor and cognitive symptoms. PD diagnosis is a challenging task since its symptoms are very similar to other diseases such as normal ageing and…
Passive and non-obtrusive health monitoring using wearables can potentially bring new insights into the user's health status throughout the day and may support clinical diagnosis and treatment. However, identifying segments of free-living…
This study utilized the Tempotron, a robust classifier based on a third-generation neural network model, for pulse shape discrimination. By eliminating the need for manual feature extraction, the Tempotron model can process pulse signals…
Lung ultrasound imaging is reaching growing interest from the scientific community. On one side, thanks to its harmlessness and high descriptive power, this kind of diagnostic imaging has been largely adopted in sensitive applications, like…
The first direct detection of gravitational waves may be made through observations of pulsars. The principal aim of pulsar timing array projects being carried out worldwide is to detect ultra-low frequency gravitational waves (f ~ 10^-9 to…
Congenital heart disease (CHD) is a critical condition that demands early detection, particularly in infancy and childhood. This study presents a deep learning model designed to detect CHD using phonocardiogram (PCG) signals, with a focus…
Pulsar surveys generate millions of candidates per run, overwhelming manual inspection. This thesis builds a deep learning pipeline for radio pulsar candidate selection that fuses array-derived features with image diagnostics. From…
Prenatal ultrasound evaluates fetal growth and detects congenital abnormalities during pregnancy, but the examination of ultrasound images by radiologists requires expertise and sophisticated equipment, which would otherwise fail to improve…
Using public pulse time-of-arrival data from five pulsar timing arrays (PTAs), we search for a stationary, isotropic, and unpolarized nHz stochastic gravitational-wave background (SGWB). This analysis is more sensitive than previous…
Sleep is among the most important factors affecting one's daily performance, well-being, and life quality. Nevertheless, it became possible to measure it in daily life in an unobtrusive manner with wearable devices. Rather than camera…
Intrapartum cardiotocography (CTG) is widely used for fetal monitoring during labor, yet its interpretation suffers from high inter-observer variability and limited predictive accuracy. Deep learning approaches have been constrained by the…
Transcranial photobiomodulation (tPBM) therapy is an emerging, non-invasive neuromodulation technique that has demonstrated considerable potential in the field of neuropsychiatric disorders. Several studies have found that pulsed wave (PW)…