Abstract Machine learning technologies and translation of artificial intelligence tools to
enhance the patient experience are changing obstetric and maternity care. An increasing …

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

With the emergence of the Internet of Things (IoT), investigation of different diseases in
healthcare improved, and cloud computing helped to centralize the data and to access …

Brain-computer interface (BCI) enables the control of external devices using signals from the
brain, offering immense potential in assisting individuals with neuromuscular disabilities …

Abstract Convolutional Neural Networks (CNNs) are frequently used for image classification.
This is crucial for the biomedical image classification used for automatic diagnosis in …

Brain stress monitoring has emerged as a critical research area for understanding and
managing stress and neurological health issues. This burgeoning field aims to provide …

The application of deep learning models in medical diagnosis has showcased considerable
efficacy in recent years. Nevertheless, a notable limitation involves the inherent lack of …

Fetal heart rate monitoring based on fetal heart rate (FHR) is an important diagnostic tool for
evaluating fetal health in late pregnancy. Currently, intelligent cardiotocography (CTG) …

CTG (Cardiotocography) is an effective tool for fetal status assessment. Clinically, doctors
mainly evaluate the health of fetus by observing FHR (fetal heart rate). The rapid …

This study to solve the information storage problem in the current medical system analyzes
the privacy and security effects of the blockchain (BC) in the Internet of Medical Things …