Still moving toward automation of the systematic review process: a summary of discussions at the third meeting of the International Collaboration for Automation of Systematic Reviews (ICASR)

The third meeting of the International Collaboration for Automation of Systematic Reviews (ICASR) was held 17–18 October 2017 in London, England. ICASR is an interdisciplinary group whose goal is to maximize the use of technology for conducting rapid, accurate, and efficient systematic reviews of scientific evidence. The group seeks to facilitate the development and widespread acceptance of automated techniques for systematic reviews. The meeting’s conclusion was that the most pressing needs at present are to develop approaches for validating currently available tools and to provide increased access to curated corpora that can be used for validation. To that end, ICASR’s short-term goals in 2018–2019 are to propose and publish protocols for key tasks in systematic reviews and to develop an approach for sharing curated corpora for validating the automation of the key tasks

Safer tattooing interventions in prisons: A systematic review and call to action

© 2018 The Author(s). Background: Worldwide more than ten million people are detained at any given time. Between 5 and 60% of people experiencing incarceration report receipt of a tattoo in prison - mostly clandestine, which is associated with risks of blood-borne infections (BBIs). Although safer tattooing techniques are effective in preventing BBI transmission and available to the general population, there is limited knowledge about the impact of safer tattooing strategies in prisons in terms of health outcomes, changes in knowledge and behaviors, and best practice models for implementation. The objective of this research was to identify and review safer tattooing interventions. Methods: We conducted a systematic review of the literature. Studies of all design types were included if they were published until 27 June 2018, the population was incarcerated adults, they reported quantitative outcomes, and were published in English, French, or Spanish. Results: Of 55 papers retrieved from the initial search, no peer-reviewed article was identified. One paper from the grey literature described a multi-site pilot project in Canada. Its evaluation suggested that the project was effective in enhancing knowledge of incarcerated people and prison staff on standard precautions, had the potential to reduce harm, provided vocational opportunities, and was feasible although enhancements were needed to improve implementation issues and efficiency. Conclusions: Although access to preventive services, including to safer tattooing interventions, is a human right and recommended by United Nations agencies as part of a comprehensive package of harm reduction interventions in prisons, this review identified only a few promising strategies for safer tattooing interventions in carceral settings. We call upon governments, criminal justice authorities, non-governmental organizations, and academic institutions to implement safer tattooing projects that adhere to the following guiding principles: i) integration of methodologically-rigorous implementation research; ii) involvement of key stakeholders (incarcerated people, prison authorities, research partners) in the project design, implementation, and research; iii) integration into a comprehensive package of BBI prevention, treatment, and care, using a stepwise approach that considers local resources and acceptability; and iv) publication and dissemination of findings, and scaling up efforts. Prospero Registration: CRD42017072502

Combining heterogeneous sources in an interactive multimedia content retrieval model

Interactive multimodal information retrieval systems (IMIR) increase the capabilities of traditional search systems, by adding the ability to retrieve information of different types (modes) and from different sources. This article describes a formal model for interactive multimodal information retrieval. This model includes formal and widespread definitions of each component of an IMIR system. A use case that focuses on information retrieval regarding sports validates the model, by developing a prototype that implements a subset of the features of the model. Adaptive techniques applied to the retrieval functionality of IMIR systems have been defined by analysing past interactions using decision trees, neural networks, and clustering techniques. This model includes a strategy for selecting sources and combining the results obtained from every source. After modifying the strategy of the prototype for selecting sources, the system is reevaluated using classification techniques.This work was partially supported by eGovernAbility-Access project (TIN2014-52665-C2-2-R)

Evolução da Ferramenta RESuLT para Auxiliar a Execução de Revisões Sistemáticas da Literatura

TCC(graduação) - Universidade Federal de Santa Catarina. Centro Tecnológico. Ciências da Computação.A revisão sistemática é uma forma de executar revisões da literatura de forma não tendenciosa seguindo um processo sistemático. Na prática ela requer um esforço considerável, principalmente na execução das buscas e na seleção de estudos. Para auxiliar este tipo de revisão existem várias ferramentas que automatizam a busca em diversas bases digitais e permitem que a revisão seja conduzida por mais de um pesquisador. Porém, nenhuma ferramenta encontrada consegue de fato abranger por completo a automatização da busca e a revisão colaborativa. Entre estas ferramentas encontra-se a RESuLT, criada para auxiliar na execução de revisões sistemáticas na Engenharia de Software. A ferramenta RESuLT é desenvolvida para suportar um processo de RSL seguindo as fases de planejamento e execução da revisão do processo proposto por Kitchenham (2007). A RESuLT possibilita a integração de parte do processo de RSL em uma única ferramenta, auxiliando desde a montagem da string de busca à execução paralela das buscas nas bases digitais. Porém, observou-se que as bases pesquisas são incompletas e falta suporte a um processo de seleção de artigos de forma colaborativa. O objetivo deste trabalho visa melhorar a ferramenta RESuLT analisando as bases já existentes, melhorando o acesso as bases digitais disponíveis para a busca e a implementação de uma revisão de forma colaborativa. A qualidade da ferramenta é avaliada em termos da precisão e recall e também por meio de uma inspeção por um painel de envolvidos. Com isso espera-se melhorar a consulta e a resposta para o pesquisador com as API’s atualmente disponíveis, possibilitar mais opções de bases de pesquisas simultâneas e facilitar o processo de seleção de artigos relevantes usando um processo colaborativo. Desta forma, espera-se melhorar a ferramenta de forma a torná-la mais completa, fácil e eficiente para a execução de uma revisão sistemática

Serving Evidence Syntheses: Improving literature retrieval in systematic reviews

A new method allows medical information specialists to perform literature research for systematic reviews in a shorter time with better results

Developing automated meta-research approaches in the preclinical Alzheimer's disease literature

Alzheimer’s disease is a devastating neurodegenerative disorder for which there is no cure. A crucial part of the drug development pipeline involves testing therapeutic interventions in animal disease models. However, promising findings in preclinical experiments have not translated into clinical trial success. Reproducibility has often been cited as a major issue affecting biomedical research, where experimental results in one laboratory cannot be replicated in another. By using meta-research (research on research) approaches such as systematic reviews, researchers aim to identify and summarise all available evidence relating to a specific research question. By conducting a meta-analysis, researchers can also combine the results from different experiments statistically to understand the overall effect of an intervention and to explore reasons for variations seen across different publications. Systematic reviews of the preclinical Alzheimer’s disease literature could inform decision making, encourage research improvement, and identify gaps in the literature to guide future research. However, due to the vast amount of potentially useful evidence from animal models of Alzheimer’s disease, it remains difficult to make sense of and utilise this data effectively. Systematic reviews are common practice within evidence based medicine, yet their application to preclinical research is often limited by the time and resources required. In this thesis, I develop, build-upon, and implement automated meta-research approaches to collect, curate, and evaluate the preclinical Alzheimer’s literature. I searched several biomedical databases to obtain all research relevant to Alzheimer’s disease. I developed a novel deduplication tool to automatically identify and remove duplicate publications identified across different databases with minimal human effort. I trained a crowd of reviewers to annotate a subset of the publications identified and used this data to train a machine learning algorithm to screen through the remaining publications for relevance. I developed text-mining tools to extract model, intervention, and treatment information from publications and I improved existing automated tools to extract reported measures to reduce the risk of bias. Using these tools, I created a categorised database of research in transgenic Alzheimer’s disease animal models and created a visual summary of this dataset on an interactive, openly accessible online platform. Using the techniques described, I also identified relevant publications within the categorised dataset to perform systematic reviews of two key outcomes of interest in transgenic Alzheimer’s disease models: (1) synaptic plasticity and transmission in hippocampal slices and (2) motor activity in the open field test. Over 400,000 publications were identified across biomedical research databases, with 230,203 unique publications. In a performance evaluation across different preclinical datasets, the automated deduplication tool I developed could identify over 97% of duplicate citations and a had an error rate similar to that of human performance. When evaluated on a test set of publications, the machine learning classifier trained to identify relevant research in transgenic models performed was highly sensitive (captured 96.5% of relevant publications) and excluded 87.8% of irrelevant publications. Tools to identify the model(s) and outcome measure(s) within the full-text of publications may reduce the burden on reviewers and were found to be more sensitive than searching only the title and abstract of citations. Automated tools to assess risk of bias reporting were highly sensitive and could have the potential to monitor research improvement over time. The final dataset of categorised Alzheimer’s disease research contained 22,375 publications which were then visualised in the interactive web application. Within the application, users can see how many publications report measures to reduce the risk of bias and how many have been classified as using each transgenic model, testing each intervention, and measuring each outcome. Users can also filter to obtain curated lists of relevant research, allowing them to perform systematic reviews at an accelerated pace with reduced effort required to search across databases, and a reduced number of publications to screen for relevance. Both systematic reviews and meta-analyses highlighted failures to report key methodological information within publications. Poor transparency of reporting limited the statistical power I had to understand the sources of between-study variation. However, some variables were found to explain a significant proportion of the heterogeneity. Transgenic animal model had a significant impact on results in both reviews. For certain open field test outcomes, wall colour of the open field arena and the reporting of measures to reduce the risk of bias were found to impact results. For in vitro electrophysiology experiments measuring synaptic plasticity, several electrophysiology parameters, including magnesium concentration of the recording solution, were found to explain a significant proportion of the heterogeneity. Automated meta-research approaches and curated web platforms summarising preclinical research could have the potential to accelerate the conduct of systematic reviews and maximise the potential of existing evidence to inform translation