Ranks distinct AI gain and problem claims from the published record. Scores reward impact, independent source strength, scale, confidence, and recency.
In a peer-reviewed study published June 25 2024, researchers surveyed 87 SMEs in France about their use of generative AI tools during the COVID-19 pandemic, geopolitical crises, and economic slowdown. Using a pre-tested survey and WarpPLS 7.0 modelling, they tested how generative AI and entrepreneurial orientation relate to entrepreneurial resilience under market turbulence.
In February 2024 the Council and European Parliament agreed on the AI Act, a risk-based regulation intended to ensure ethical and responsible AI use across the EU single market. The article examines the governance system in the April 2024 version of the text, noting the creation of a European Artificial Intelligence Office and planned Board, advisory forum, scientific panel, and national competent authorities.
In mid-2024, researchers reported results from a large-scale survey and follow-up interviews of innovation managers in the USA to assess how AI is actually used in innovation. They found adoption is high and widespread, with AI applied in more than half of surveyed firms' innovation projects and concentrated in the development stage rather than idea or commercialization stages.
This peer-reviewed paper models AI's macroeconomic impact as task-level automation and complementarity, using Hulten's theorem to translate the fraction of tasks impacted and average cost savings into GDP and TFP effects. Using existing exposure estimates, it calculates no more than a 0.66% TFP increase over 10 years, then revises down to less than 0.53% after accounting for the shift from easy-to-learn to hard-to-learn tasks.
Axial dissections of the thoracic artery are common causes of death in people diagnosed with aortic dissection; however, decisions to intervene on ascending thoracic aortic patients are determined by the size of the ascending thoracic aorta based on its diameter. Diameter-based criteria fail to take into consideration the biomechanical properties of the aorta as well as other characteristics of the patient, and finite element analysis (in determining aortic wall stresses) would ideally address the issues associated with today's diameter-based criteria.
Background Large language model (LLM)-generated hospital courses are increasingly integrated into electronic health records (EHRs), yet their accuracy and safety in pediatric populations remain poorly characterized. Objective To evaluate the accuracy, text quality, and perceived potential harm of EHR-integrated and LLM-generated hospital courses in pediatric inpatient care during early clinical implementation.
Recent years have witnessed considerable progress in computer-aided drug discovery, driven by the incorporation of computational technologies within both academic and pharmaceutical environments. This evolution is marked by a significant accumulation of data pertaining to detailed three-dimensional structural information, ligand properties, and their interactions with therapeutic targets.
Background Renal transplantation is the preferred treatment for end-stage chronic kidney disease but requires lifelong immunosuppression, increasing the risk of infections such as urinary tract infection (UTI). UTI in kidney transplant recipients can lead to serious complications, including acute kidney injury, reduced graft survival, and increased mortality.
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