The application of innovative technologies, and in particular of wearable devices, can
potentially transform the field of antenatal care with the aim of improving maternal and new …

Healthcare digitalization requires effective applications of human sensors, when various
parameters of the human body are instantly monitored in everyday life due to the Internet of …

The Internet of Things (IoT) has positioned itself globally as a dominant force in the
technology sector. IoT, a technology based on interconnected devices, has found …

This study presents the concept of a computationally efficient machine learning (ML) model
for diagnosing and monitoring Parkinson's disease (PD) using rest-state EEG signals (rs …

Early identification of acute stroke lowers the fatality rate since clinicians can quickly decide
on a quick decision of therapy. Brain computed tomography (CT) was one of the imaging …

Pre-eclampsia (PET) is a hypertensive disease that occurs during pregnancy or in the
postpartum period. It complicates 2% to 8% of all pregnancies and is one of the causes of …

The study presents a bio-inspired chaos sensor model based on the perceptron neural
network for the estimation of entropy of spike train in neurodynamic systems. After training …

Purpose This study aims to investigate the relationship between patient satisfaction (PS) and
the parameters in healthcare and supply chain management (HLSCM) …

Maternal health remains a critical global health challenge, with disparities in access to care
and quality of services contributing to high maternal mortality and morbidity rates. Artificial …

Abstract The implementation of Artificial Intelligence (AI) in healthcare is enhancing
diagnostic accuracy in clinical setups. The use of AI in healthcare is steadily increasing with …