1,720,988 research outputs found
The role of artificial intelligence in maternal and child health: Progress, controversies, and future directions.
Get PDFThis debate paper examines the transformative potential of Artificial Intelligence (AI), specifically through Machine Learning (ML), in enhancing preventive measures in maternal and child health (MCH). With the proliferation of Big Data, ML has become crucial in handling complex, non-linear interactions among health determinants to not only predict but also prevent adverse outcomes. This paper underscores AI's applications in early interventions that could decrease the incidence of MCH issues. It reviews technological advancements while addressing ethical, practical, and data-related challenges in applying AI in preventive healthcare. Emphasis is placed on recent supervised, unsupervised, and reinforcement learning applications that significantly advance preventive care, particularly in low-resource settings. The manuscript discusses the development of AI models for early diagnosis, comprehensive risk assessments, and customized preventive interventions, while highlighting challenges like data diversity, privacy issues, and integrating multimodal health data
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe 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
Get PDF“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
Get PDFWe 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
Get PDFWe 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
Recommended from our members
Modeling, Prediction, and Inference: Applications in Social and Infectious Disease Epidemiology
No full textEpidemiology is at an exciting stage. Methods and techniques from other areas, such as data science, combined with advances in classic fields, such as Bayesian statistics, provide a new set of tools to explore epidemiological questions. In this dissertation, with collaboration from my committee members, I applied some of these new tools to three distinct epidemiological problems. My work contributes to the literature by showing how the synthesis and arbitrage of ideas from other fields can be adapted to diverse epidemiological settings.
First, I combined innovations in Bayesian statistics with advances in computation and statistical programming languages to jointly model racial/ethnic disparities in premature mortality at a scale not previously possible. Specifically, I used the shared component model to decompose premature mortality risk in non-Hispanic black and white Americans in the contiguous US into race-specific and shared components. I found that the majority of geographic variation in black-specific premature mortality risk was not shared with the white population, despite half of the geographic variation in white risk being shared with the black population.
Second, I estimated rates of missingness in a new method of spatiotemporally dense data collection called digital phenotyping. This type of data collection uses smartphones and does not require active participation by the user, making it a potentially useful data collection mechanism for epidemiologists interested in individual-level behavior. I found rates of missingness to be non-trivial (16-18%), increasing only slowly over time (0.5-1% per week), and largely uncorrelated with phone type or common demographic characteristics.
Third, I borrowed techniques from data science to systematically evaluate the performance of different classes and parameterizations of models in predicting dengue in Thailand at the province-level. Specifically, I compared an array of autoregressive models with regularized linear models. We found that model predictive performance varies greatly by both area and forecasting horizon with no single model or class of model performing best in every area or across all time horizons.
In summary, as data science and other fields become embedded in epidemiology, there is a large potential for the use of new tools to answer traditional and new public health questions.digital epidemiology; health inequalities; digital phenotyping; spatial epidemiolog
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
Author-wise bibliometric analysis based on entropy.
No full textAuthor-wise bibliometric analysis based on entropy.</p
- …
