1,721,001 research outputs found
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
The Role of Artificial Intelligence and Machine Learning Models in Antimicrobial Stewardship in Public Health: A Narrative Review
Full text linkAntimicrobial resistance (AMR) poses a critical global health threat, necessitating innovative approaches in antimicrobial stewardship (AMS). Artificial intelligence (AI) and machine learning (ML) have emerged as transformative tools in this domain, enabling data-driven interventions to optimize antibiotic use and combat resistance. This comprehensive review explores the multifaceted role of AI and ML models in enhancing antimicrobial stewardship efforts across healthcare systems. AI-powered predictive analytics can identify patterns of resistance, forecast outbreaks, and guide personalized antibiotic therapies by leveraging large-scale clinical and epidemiological data. ML algorithms facilitate rapid pathogen identification, resistance profiling, and real-time monitoring, enabling precise decision making. These technologies also support the development of advanced diagnostic tools, reducing the reliance on broad-spectrum antibiotics and fostering timely, targeted treatments. In public health, AI-driven surveillance systems improve the detection of AMR trends and enhance global monitoring capabilities. By integrating diverse data sources—such as electronic health records, laboratory results, and environmental data—ML models provide actionable insights to policymakers, healthcare providers, and public health officials. Additionally, AI applications in antimicrobial stewardship programs (ASPs) promote adherence to prescribing guidelines, evaluate intervention outcomes, and optimize resource allocation. Despite these advancements, challenges such as data quality, algorithm transparency, and ethical considerations must be addressed to maximize the potential of AI and ML in this field. Future research should focus on developing interpretable models and fostering interdisciplinary collaborations to ensure the equitable and sustainable integration of AI into antimicrobial stewardship initiatives
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Emergency colon cancer diagnosis in people with mental health conditions: a population-based cohort study in northern Italy
Full text linkBackground Individuals with mental health conditions may experience disparity in cancer diagnosis and health outcomes. This study aims to examine diagnostic pathways and mortality in patients with colon cancer with pre-existing mental health conditions. Methods A population-based cohort study on colon cancer cases diagnosed in 2014-2020 in the provinces of Milan and Lodi, using linked cancer registration and health data. We examined cancer diagnostic pathways (screening, emergency presentation (EP), inpatient/outpatient visits) and short-term mortality in patients with and without pre-existing mental health conditions, accounting for physical comorbidities and sociodemographic factors. Mental health conditions were systematically categorised into distinct groups according to the International Classification of Diseases, 10th Revision. Results Out of 11 429 patients with colon cancer, 16.2% had a pre-existing mental health condition. Individuals with mental health conditions versus those without had a higher risk of cancer diagnosis following EP: 43.8% versus 33.8%, adjusted OR (aOR) 1.32, 95% CI 1.19 to 1.47. EP risk was higher for patients with diagnoses of dementia and related cognitive conditions (aOR 1.69, 95% CI 1.41 to 2.03), substance use/ behavioural syndromes/personality-related conditions (aOR 1.92, 95% CI 1.34 to 2.75) and anxiety (aOR 1.44, 95% CI 1.16 to 1.79). The likelihood of screening-detected cancer was lower (4.6% vs 9.1%; aOR 0.78, 95% CI 0.60 to 0.99), especially for dementia and related cognitive conditions (aOR 0.27, 95% CI 0.08 to 0.86). Short-term mortality was higher in patients with cancer with mental health conditions than in those without. Conclusion Mental health conditions were associated with a lower likelihood of screening and a higher risk of emergency cancer diagnosis. Tailored strategies are warranted to enhance cancer diagnosis for the non-negligible group of individuals with mental health conditions
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
Knowledge and attitudes towards Zika virus: an Italian nation-wide cross-sectional study
No full textBACKGROUND: Zika virus (ZIKV) is an arthropod-borne virus transmitted through infected mosquitos. The aim of this Italian nation-wide study was to evaluate general population's knowledge and attitudes towards ZIKV, its transmission, and travel-related preventive measures. METHODS: This cross-sectional study was conducted between July and August 2017, through a validated questionnaire. Predictors of knowledge were analysed through multivariate regression. RESULTS: Among 1119 respondents, 20% and 71% knew etiological agent and transmission route of ZIKV infection, respectively. Approximately 43% ignored the preventive measures to be taken after returning from endemic areas. At multivariate analysis, predictors of poor knowledge were age, living in Central or South Italy and Islands, being poorly educated, having never heard of or attended a travel clinic. CONCLUSIONS: This study captures an overall poor knowledge of Zika among general public. This research highlights the need of designing and implementing measures to improve travellers' awareness and protection against ZIKV
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