Latest AI and machine learning research in prevention of medical errors for healthcare professionals.
Between 2010 and 2021, fentanyl and stimulants co-involved deaths increased from 0.6% to 32.3% of al...
The course of psychotic disorders typically involves relapses. Early warning signs vary between indi...
Rare events, despite their infrequency, often carry critical information and require immediate att...
Prenatal ultrasound evaluates fetal growth and detects congenital abnormalities during pregnancy, ...
Traditional communication signal detection heavily relies on manually designed features, making it d...
This study presents a convolutional neural network (CNN)-based method for the classification and rec...
Metabolic syndrome (MetS) has a significant impact on health. MetS is the umbrella term for a group...
The rapid development and integration of interconnected healthcare devices and communication network...
Phishing is an online identity theft technique where attackers steal users personal information, l...
Ensuring trustworthiness is fundamental to the development of artificial intelligence (AI) that is...
Federated learning has become a promising solution for collaboration among medical institutions. H...
The rapid identification of medical emergencies through digital communication channels remains a c...
The recent rise of semantic-style communications includes the development of goal-oriented communi...
Federated Learning (FL) enables multiple clients to train a collaborative model without sharing th...
In the early stage of an infectious disease outbreak, public health strategies tend to gravitate t...
Advances in imaging technologies have revolutionised the medical imaging and healthcare sectors, l...
Federated graph learning (FGL) has gained significant attention for enabling heterogeneous clients...
This paper proposes a novel federated algorithm that leverages momentum-based variance reduction w...
One of the key goals of artificial intelligence (AI) is the development of a multimodal system tha...
This paper investigates the adversarial robustness of Deep Neural Networks (DNNs) using Informatio...
The visible orientation of human eyes creates some transparency about people's spatial attention a...