In a majority–minority classification problem, class imbalance in the dataset (s) can
dramatically skew the performance of classifiers, introducing a prediction bias for the …

Background: Artificial intelligence (AI) provides opportunities to identify the health risks of
patients and thus influence patient safety outcomes. Objective: The purpose of this …

Objectives: To summarise current research that takes advantage of “Big Data” in health and
biomedical informatics applications. Methods: Survey of trends in this work, and exploration …

We identify and describe nine key, short-term, challenges to help healthcare organizations,
health information technology developers, researchers, policymakers, and funders focus …

Severe class imbalance between majority and minority classes in Big Data can bias the
predictive performance of Machine Learning algorithms toward the majority (negative) class …

Importance Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia, and its
early detection could lead to significant improvements in outcomes through the appropriate …

Recent advancements in generative artificial intelligence, particularly using large language
models (LLMs), are gaining increased public attention. We provide a perspective on the …

The aim of this study was to analyse electronic health record–related patient safety incidents
in the patient safety incident reporting database in fully digital hospitals in Finland. We …

Despite the renewed interest in Artificial Intelligence-based clinical decision support systems
(AI-CDS), there is still a lack of empirical evidence supporting their effectiveness. This …

The generation of earthquakes at depths exceeding 60 km remains debated, as rocks at
such depths are anticipated to be ductile. Seismological investigations have revealed a …