Artificial intelligence and machine learning (AI-ML) implies the ability of machines to “think”
and includes the ability of computers or programs to “learn” with experience. 1 Smartphones …

Objective Linguistic diversity has the potential to create barriers for limited language
proficiency (LLP) patients when navigating the healthcare system. When a verified …

With increasing computing power, artificial intelligence (AI) and machine learning (ML) have
prospered, which facilitate the analysis of large datasets, especially those found in critical …

The development of artificial intelligence methods has impacted therapeutics, personalized
diagnostics, drug discovery, and medical imaging. Although, in many situations, AI clinical …

Cutting-edge technologies are leading to a profound transformation of healthcare (1, 2).
Among the most promising advancements is the integration of artificial intelligence (AI) into …

OBJECTIVE: Perform a scoping review of supervised machine learning in pediatric critical
care to identify published applications, methodologies, and implementation frequency to …

Artificial intelligence (AI) has long been discussed as a transformative tool in health care,
promising to revolutionize all aspects of patient care and even our broader health care …

Background Perhaps nowhere else in the healthcare system than in the intensive care unit
environment are the challenges to create useful models with direct time-critical clinical …

In the realm of cybersecurity, the evaluation and enhancement of cyber resilience are
paramount to safeguarding nations and organizations against evolving digital threats. This …

Background: Critical congenital heart disease (cCHD)—requiring cardiac intervention in the
first year of life for survival—occurs globally in 2-3 of every 1000 live births. In the critical …