1,720,969 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
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
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
Influenza Vaccination of Nurses and Other Health Care Workers in Different Occupational Settings: A Classic and AI Mixed Approach for Time-to-Event Data
Full text linkBackground: Seasonal influenza currently remains a major public health concern for the community and, in particular, the health care worker (HCW). According to the World Health Organization, HCWs are among the high-risk categories for which vaccination is recommended, due to the derived absenteeism, productivity loss, and high probability of transmitting the disease to vulnerable individuals or patients. Therefore, an HCW vaccination policy should be adopted by every health care provider. There is growing evidence that a time effect of the vaccination event is probable, which may influence vaccine effectiveness. We designed and conducted an observational study to investigate the time to anti-influenza vaccination event of different categories of HCWs belonging to different occupational settings in a tertiary hospital during three seasons in order to retrieve some insight about HCW prioritization when designing vaccination campaigns. Materials and Methods: We retrospectively analyzed the results of two HCW anti-influenza vaccination campaigns (2022 and 2023) to assess any difference regarding job typology and unit typology (critical care, surgical, medical, service). We first fitted a classic Cox proportional hazard model and then an AI random forest model to assess variable importance. We used R, RStudio, and the survex package. Results: Overall, other HCWs reported a lower vaccination rate compared to nurses (HR 0.77; 95%CI 0.62–0.97), and service unit personnel appeared to more likely be vaccinated (HR 1.42; 95%CI 1.01–1.99) compared to those belonging to the critical care units. As expected, older workers tended to be vaccinated more frequently (HR 1.70 for the (46, 65] category compared to the younger one; 95%CI 1.39–2.09). The variable importance analysis showed consistent superiority of the ward typology and age category variables with respect to time. During the entire timeline, the ward typology appeared to be more important than the HCW typology. Conclusions: Our results suggest a prioritization policy based firstly on the unit typology followed by the job typology for HCW anti-influenza campaigns
Occupational Exposure to Biological Agents in a Typical Restaurant Setting: Is a Photocatalytic Air Purifier Helpful?
Full text linkAccording to many national legislations, biological agents represent an occupational hazard that must be managed in order to ensure safety at workplace. Bioaerosols have been associated to many pathological conditions but, despite many efforts, precise threshold limit values (TLV) are still undefined. We planned and conducted an environmental study concerning a typical restaurant that aimed to evaluate: (1) the occupational exposure to bacterial and fungal bioaerosol; (2) the efficacy of a photocatalytic air purifier device in mitigating such exposure. This observational study evaluated two dining rooms (Area 1 and Area 2) of a restaurant which can be considered typical during two consecutive weeks. Based on a national protocol, we monitored total bacterial and mycotic loads searching for two typologies of bacteria, psychrophilic bacteria (environmental contamination) along with mesophilic bacteria (human or animal origin source), and two types of fungi, mold and yeast. Baseline total bacterial load was 346.8 CFU/m(3) for Area 1 and 412.9 CFU/m(3) for Area 2. When the sanitizing device was operative, the total bacterial load decreased to 202.7 CFU/m(3) (-41.50%-p value: <0.01) for Area 1 and to 342.2 CFU/m(3) (-1-17.10%-p value: 0.06) for Area 2. Considering the fungal load, the mean baseline value was 189.7 CFU/m(3) for Area 1 and 141.1 CFU/m(3) for Area 2. When the device was kept on, the total fungal load was 108.0 CFU/m(3) (-4-43.10%-p value: 0.055) for Area 1 and 205.0 CFU/m(3) (+45.30%-p value: 0.268) for Area 2. Our findings supported the conclusion that, concerning the occupational risk derived from biological agents, a typical restaurant should be considered relatively safe. In order to mitigate or limit any possible increase of such risk, a photocatalytic device may be helpful, but not against the pollution caused by mold or yeasts. Our research also reaffirmed the need of further research assessing the kind of relationship between diseases and exposure levels, before considering the need of setting precise threshold limit values
Prediction Models for Intrauterine Growth Restriction Using Artificial Intelligence and Machine Learning: A Systematic Review and Meta-Analysis
Full text linkBackground: IntraUterine Growth Restriction (IUGR) is a global public health concern and has major implications for neonatal health. The early diagnosis of this condition is crucial for obtaining positive outcomes for the newborn. In recent years Artificial intelligence (AI) and machine learning (ML) techniques are being used to identify risk factors and provide early prediction of IUGR. We performed a systematic review (SR) and meta-analysis (MA) aimed to evaluate the use and performance of AI/ML models in detecting fetuses at risk of IUGR. Methods: We conducted a systematic review according to the PRISMA checklist. We searched for studies in all the principal medical databases (MEDLINE, EMBASE, CINAHL, Scopus, Web of Science, and Cochrane). To assess the quality of the studies we used the JBI and CASP tools. We performed a meta-analysis of the diagnostic test accuracy, along with the calculation of the pooled principal measures. Results: We included 20 studies reporting the use of AI/ML models for the prediction of IUGR. Out of these, 10 studies were used for the quantitative meta-analysis. The most common input variable to predict IUGR was the fetal heart rate variability (n = 8, 40%), followed by the biochemical or biological markers (n = 5, 25%), DNA profiling data (n = 2, 10%), Doppler indices (n = 3, 15%), MRI data (n = 1, 5%), and physiological, clinical, or socioeconomic data (n = 1, 5%). Overall, we found that AI/ML techniques could be effective in predicting and identifying fetuses at risk for IUGR during pregnancy with the following pooled overall diagnostic performance: sensitivity = 0.84 (95% CI 0.80–0.88), specificity = 0.87 (95% CI 0.83–0.90), positive predictive value = 0.78 (95% CI 0.68–0.86), negative predictive value = 0.91 (95% CI 0.86–0.94) and diagnostic odds ratio = 30.97 (95% CI 19.34–49.59). In detail, the RF-SVM (Random Forest–Support Vector Machine) model (with 97% accuracy) showed the best results in predicting IUGR from FHR parameters derived from CTG. Conclusions: our findings showed that AI/ML could be part of a more accurate and cost-effective screening method for IUGR and be of help in optimizing pregnancy outcomes. However, before the introduction into clinical daily practice, an appropriate algorithmic improvement and refinement is needed, and the importance of quality assessment and uniform diagnostic criteria should be further emphasized
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
The determinants of expert opinion in the development of care pathways: insights from an exploratory cluster analysis
Full text linkBACKGROUND: We performed a secondary exploratory cluster analysis on the data collected from the validation phase of the study leading to the development of the model care pathway (CP) for Myasthenia Gravis (MG), in which a panel of 85 international experts were asked some characteristics about themselves and their opinion about the model CP. Our aim was to identify which characteristics of the experts play a role in the genesis of their opinion. METHODS: We extracted the questions probing an opinion and those describing a characteristic of the expert from the original questionnaire. We performed a multiple correspondence analysis (MCA) and a subsequent hierarchical clustering on principal component (HCPC) on the opinion variables, integrating the characteristic variables as supplementary (predicted). RESULTS: After reducing the dimensionality of the questionnaire to three dimensions we noticed that the not-appropriateness judgement of the clinical activities may overlap with the completeness one. From the HCPC it seems that the working setting of the expert may play a crucial role in determining the opinion about the setting of the sub-processes of MG: shifting from a cluster where the experts do not work in sub-specialist settings to one where the experts are working in them, the opinion changes accordingly from a mono-disciplinary setting to a multi-disciplinary one. Another interesting result is that the experience in neuromuscular diseases (NMD) measured in years and the expert typology (whether general neurologist or NMD expert) seem not to contribute significantly to the opinions. CONCLUSIONS: These findings might indicate a poor ability of the expert to discriminate what is not appropriate from what is not complete. Also, the opinion of the expert might be influenced by the working setting, but not by the experience in NMD (as measured in years).sponsorship: The principal study [9] was funded with a grant from UCB pharma to European Pathway Association (EPA). (UCB pharma)status: Publishe
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