Latest AI and machine learning research in cultural competence for healthcare professionals.
In Low- and Middle- Income Countries (LMICs), machine learning (ML) and artificial intelligence (AI)...
BACKGROUND: Lower extremity arterial Doppler (LEAD) and duplex carotid ultrasound studies are used f...
In this study, we conducted a citation network analysis of the to elucidate the scope, evolution, a...
Unsupervised Domain Adaptation (UDA) makes predictions for the target domain data while labels are o...
The antigenic diversity of influenza A viruses (IAV) circulating in swine challenges the development...
In recent years, the prevalence of technological advances has led to an enormous and ever-increasing...
Ensemble learning methods combine multiple models to improve performance by exploiting their diversi...
Artificial intelligence (AI) is a potentially reliable assistant in the diagnosis of osteoporosis. T...
Modern experimental technologies can assay large numbers of biological sequences, but engineered pro...
There is clear evidence to suggest that diabetes does not affect all populations equally. Among adul...
Artificial intelligence (AI) is increasingly employed in health care fields such as oncology, radiol...
PURPOSE: RobotReviewer is a machine learning system for semi-automated assistance in risk of bias as...
The mortality prediction of diverse rare diseases using electronic health record (EHR) data is a cru...
RATIONALE: This paper aims to show how the focus on eradicating bias from Machine Learning decision-...
Cardiovascular disorders cause nearly one in three deaths in the United States. Short- and long-term...
RATIONALE, AIMS AND OBJECTIVES: Artificial intelligence and big data are more and more used in medic...
BACKGROUND: The rapid integration of Artificial Intelligence (AI) into the healthcare field has occu...
Whole-body imaging of mice is a key source of information for research. Organ segmentation is a prer...
BACKGROUND: The US population is becoming more racially and ethnically diverse. Research suggests th...
Scarce or absent radiology resources impede adoption of artificial intelligence (AI) for medical ima...
Machine learning (ML) algorithms have demonstrated high diagnostic accuracy in identifying and categ...