BACKGROUND: Artificial intelligence (AI)-powered analysis of electrocardiograms (ECGs) is reshaping cardiac diagnostics, offering faster and often more accurate detection of conditions such as arrhythmias and heart failure. However, growing evidence ...
Artificial intelligence (AI), specifically large language models (LLM), have gained significant popularity over the last decade with increased performance and expanding applications. AI could improve the quality of patient care in medicine but hidden...
Large language models (LLMs) are the engines behind generative Artificial Intelligence (AI) applications, the most well-known being chatbots. As conversational agents, they-much like the humans on whose data they are trained-exhibit social bias. The ...
Coronary heart disease (CHD) is a major cardiovascular disorder that poses significant threats to global health and is increasingly affecting younger populations. Its treatment and prevention face challenges such as high costs, prolonged recovery per...
The adoption of Artificial Intelligence (AI) is reshaping the labor market; however, individuals' perceptions of its impact remain inconsistent. This study investigates the presence of the Invulnerability Bias (IB), where workers perceive that AI wil...
BACKGROUND: Risk of bias (RoB) assessment is an essential part of systematic reviews that requires reading and understanding each eligible trial and RoB tools. RoB assessment is subject to human error and is time-consuming. Machine learning-based too...
OBJECTIVE: To assess the methodological quality and the risk of bias, of studies that developed prediction models using Machine Learning (ML) techniques to estimate prenatal birthweight.
Recent advancements in artificial intelligence (AI) have significantly improved sleep-scoring algorithms, bringing their performance close to the theoretical limit of approximately 80%, which aligns with inter-scorer agreement levels. While this sugg...
Shortcut learning poses a significant challenge to both the interpretability and robustness of artificial intelligence, arising from dataset biases that lead models to exploit unintended correlations, or shortcuts, which undermine performance evaluat...
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