OBJECTIVES: To identify the lowest sensitivity and specificity that physicians and the general population consider acceptable for medical artificial intelligence (AI), relative to current human performance. METHODS: In a nationwide, cross-sectional s... read more
BACKGROUND: Artificial intelligence (AI) technologies continue to transform how we research human disease, diagnose and treat patients, and operate hospitals. However, emerging ethical dilemmas surrounding their design, use, and oversight demand both... read more
the characterization of neural activity underlying neurophysiological function presents a major challenge in computational neuroscience. Several methods have been proposed to investigate cortical network dynamics by reconstructing underlying neural a... read more
BACKGROUND: People with stroke face a high mortality risk, and an accurate prediction model is essential to the guidance of clinical decision-making in this population. Recently, with growing attention paid to machine learning (ML) in stroke care, so... read more
PURPOSE: The U.S. Hospital Price Transparency mandate requires public disclosure of machine-readable files (MRFs), yet profound data heterogeneity hinders their utility for research and consumer use. This study evaluates a novel, multi-stage computat... read more
OBJECTIVES: Healthcare systems are now funding implementation of artificial intelligence (AI) algorithms in radiology, which will change the experience of care for patients. Currently, there is still limited evidence of patient attitudes to AI implem... read more
Journal of the American Chemical Society
Apr 2, 2026
While gold nanoparticles (Au NPs) are widely employed in modern technology, their large-scale synthesis still faces challenges related to cost and sustainability. In addition, chemical contaminants are a problem when the highest purity is demanded, s... read more
Surface-enhanced Raman spectroscopy (SERS) is a promising technique for on-site detection of aqueous pollutants, whereas single-substrate SERS suffers from low separability of analogous compounds and poor accuracy. Here, we propose a multisubstrate S... read more
BACKGROUND: Effective postdischarge management is essential for maintaining disease control and improving long-term outcomes in rheumatoid arthritis (RA). Digital health technologies, particularly intelligent management platforms, provide new opportu... read more
BACKGROUND: Large language models (LLMs) now enable chatbots to engage in sensitive mental health conversations, including depression self-management. Yet their rapid deployment often overlooks how well these tools align with the priorities of people... read more
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