The ability to predict whether a peptide will get presented on Major Histocompatibility Complex (MHC) class I molecules has profound implications in designing vaccines. Numerous deep learning-based predictors for peptide presentation on MHC class I m...
OBJECTIVE: The study aimed to enhance transparency in autonomous systems by automatically generating and visualizing confidence and explanations and assessing their impacts on performance, trust, preference, and eye-tracking behaviors in human-automa...
Advances in health sciences education : theory and practice
Feb 23, 2024
The entrustment framework redirects assessment from considering only trainees' competence to decision-making about their readiness to perform clinical tasks independently. Since trainees and supervisors both contribute to entrustment decisions, we ex...
Regulatory toxicology and pharmacology : RTP
Feb 23, 2024
Risk assessment of chemicals is a time-consuming process and needs to be optimized to ensure all chemicals are timely evaluated and regulated. This transition could be stimulated by valuable applications of in silico Artificial Intelligence (AI)/Mach...
Proceedings of the National Academy of Sciences of the United States of America
Feb 22, 2024
We administer a Turing test to AI chatbots. We examine how chatbots behave in a suite of classic behavioral games that are designed to elicit characteristics such as trust, fairness, risk-aversion, cooperation, etc., as well as how they respond to a ...
As autonomous mobile robots (AMR) are introduced into workspace environments shared with people, effective human-robot communication is critical to the prevention of injury while maintaining a high level of productivity. This research presents an emp...
Public understanding of science (Bristol, England)
Feb 7, 2024
The governance of artificial intelligence (AI) is an urgent challenge that requires actions from three interdependent stakeholders: individual citizens, technology corporations, and governments. We conducted an online survey ( = 525) of US adults to ...
Experimental biology and medicine (Maywood, N.J.)
Jan 27, 2024
Bayesian networks are increasingly used to quantify the uncertainty of subjective and stochastic concepts such as trust. In this article, we propose a data-driven approach to estimate Bayesian parameters in the domain of wearable medical devices. Our...
BACKGROUND: Over the last century, technological progress has been tremendous, and technological advancement is reflected in the development of medicine. This research assessed attitudes towards surgical robots and identified correlations with willin...