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Artificial intelligence (AI) is gradually changing the planet. Data digitisation, computing infrastructure and machine learning are helping AI tools to spread across all sectors of society. This article presents the results of a bibliometric analysis of AI-related publications in the social sciences over the last ten years (2013-2022). Most of the historical publications are taken into consideration with the aim of identifying research relevance and trends in this field. The results indicate that more than 19,408 articles have been published, 85% from 2008 to 2022, showing that research in this field is increasing significantly year on year. Clear domains or disciplines of research related to AI within the social sciences can be grouped into sub-areas such as law and legal reasoning, education, economics, and ethics. The United States is the country that publishes the most (20%), followed by China (13%). The influence of AI on society is inevitable and the advances can generate great opportunities for innovation and new jobs, but in the medium term it is necessary to adequately face this transition, setting regulations and reviewing the challenges of ethics and responsibility. [ABSTRACT FROM AUTHOR]

Purpose: Gadobutrol is a 1.0 M macrocyclic magnetic resonance imaging (MRI) contrast agent. A study was performed to evaluate the efficacy and safety of gadobutrol-enhanced versus unenhanced imaging for central nervous system (CNS) lesion visualization and detection., Materials and Methods: An international, multicenter, open-label, Phase III clinical trial. Patients underwent unenhanced and gadobutrol 1.0 M-enhanced (0.1 mmol/kg BW) MR imaging using a standardized protocol. Unenhanced and combined unenhanced/gadobutrol-enhanced images were scored by three independent, blinded readers for degree of lesion enhancement, border delineation, internal morphology, and total number of lesions detected (primary efficacy variables). Exact match of the MR diagnoses with the final clinical diagnosis, detection of malignant CNS lesions, and confidence in diagnosis were secondary efficacy variables., Results: Of 343 enrolled patients, 321 were evaluated for efficacy. All primary efficacy endpoints were met: superiority was demonstrated for gadobutrol-enhanced versus unenhanced MR images (P < 0.0001 in all cases) for lesion enhancement, border delineation, and internal morphology. Noninferiority was met for mean number of lesions detected. There were improvements in the sensitivity of malignant lesion detection, without a loss in specificity, exact-match diagnostic accuracy, and reader confidence. Treatment-related adverse events were reported in 4.1% (n = 14); all were nonserious., Conclusion: Gadobutrol 1.0M is an effective and well-tolerated contrast agent for CNS MRI., (© 2014 Wiley Periodicals, Inc.)