Despite the remarkable performance of large language models (LLMs), such as generative pre-trained Transformers (GPTs), across various tasks, they often perpetuate social biases and stereotypes embedded in their training data. In this paper, we intro...
Political bias is an inescapable characteristic in news and media reporting, and understanding what political biases people are exposed to when interacting with online news is of crucial import. However, quantifying political bias is problematic. To ...
BACKGROUND: Synthetic electronic health records (EHRs) generated by large language models (LLMs) offer potential for clinical education and model training while addressing privacy concerns. However, performance variations and demographic biases in th...
Recent machine-learning (ML)-based advances in single-cell data science have enabled the stratification of human tissue donors at single-cell resolution, promising to provide valuable diagnostic and prognostic insights. However, such insights are sus...
PURPOSE: To determine how automation bias (inclination of humans to overly trust-automated decision-making systems) can affect radiologists when interpreting AI-detected cerebral aneurysm findings in time-of-flight magnetic resonance angiography (TOF...
The development and implementation of Artificial Intelligence (AI) health systems represent a great power that comes with great responsibility. Their capacity to improve and transform healthcare involves inevitable risks. A major risk in this regard ...
BACKGROUND: The deployment of Artificial Intelligence (AI) in healthcare has the potential to transform patient care through improved diagnostics, personalized treatment plans, and more efficient resource management. However, the effectiveness and fa...
Advances in artificial intelligence (AI) have achieved expert-level performance in medical imaging applications. Notably, self-supervised vision-language foundation models can detect a broad spectrum of pathologies without relying on explicit trainin...
The integration of chatbots into psychiatry introduces a novel approach to support clinical decision-making, but biases in their recommendations pose significant concerns. This study investigates potential biases in chatbot-generated recommendations ...
The Cochrane database of systematic reviews
40365867
RATIONALE: Walking difficulties are common after a stroke. During rehabilitation, electromechanical and robotic gait-training devices can help improve walking. As the evidence and certainty of the evidence may have changed since our last update in 20...