Latest AI and machine learning research in prevention of medical errors for healthcare professionals.
Robot-assisted surgery has advanced rapidly since the 1980s. However, new equipment is still needed ...
The continuous motorization of traffic has led to a sustained increase in the global number of road ...
BACKGROUND: The ability of nursing undergraduates to communicate effectively with health care provid...
The problem of quasi-synchronization (QS) for the Markovian jump master-slave neural networks with t...
BACKGROUND: Symptomatology differences of major depressive disorder (MDD) in psychiatric and general...
In this paper, we propose a distributed semi-supervised learning (DSSL) algorithm based on the extre...
Diabetes is a global public health disease projected to affect 642 million adults by 2040, with abou...
The early and accurately detection of brucellosis incidence change is of great importance for implem...
The aim of this study is to predict acute coronary syndrome (ACS) requiring revascularization in tho...
BACKGROUND: Socially assistive robots (SARs) have the potential to assist nonpharmacological interve...
This paper presents a hardware and software system to implement the task space control of an MR-cond...
Cervical cancer ranks as the second most common cancer in women worldwide. In clinical practice, col...
OBJECTIVE: Virtual reality simulators track all movements and forces of simulated instruments, gener...
: Scientific evidence supports that prevention strategies like multicomponent physical exercise help...
Understanding the risk factors that initiate cancer is essential for reducing the future cancer burd...
Chronic pharyngitis is a common disease, which has a long duration and a wide range of onset. It is ...
BACKGROUND: Suicide is a great public health challenge. Two hundred million people attempt suicide i...
Autism spectrum disorder (ASD) is common in adolescents with cerebral palsy (CP) and there is a lack...
Radiologists are expected to expediently communicate critical and unexpected findings to referring c...
PURPOSE: Frontotemporal dementia (FTD) is a neurodegenerative disorder associated with a poor progno...
Automatic modulation recognition has successfully used various machine learning methods and achieved...