2
views
0
recommends
+1 Recommend
1 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      El papel de la inteligencia artificial en las revisiones sistemáticas: implicaciones y desafíos para la divulgación científica Translated title: The role of artificial intelligence in systematic reviews: implications and challenges for scientific dissemination

      letter
      , , ,
      Angiología
      Arán Ediciones S.L.

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Related collections

          Most cited references7

          • Record: found
          • Abstract: found
          • Article: found
          Is Open Access

          Software tools to support title and abstract screening for systematic reviews in healthcare: an evaluation

          Background Systematic reviews are vital to the pursuit of evidence-based medicine within healthcare. Screening titles and abstracts (T&Ab) for inclusion in a systematic review is an intensive, and often collaborative, step. The use of appropriate tools is therefore important. In this study, we identified and evaluated the usability of software tools that support T&Ab screening for systematic reviews within healthcare research. Methods We identified software tools using three search methods: a web-based search; a search of the online “systematic review toolbox”; and screening of references in existing literature. We included tools that were accessible and available for testing at the time of the study (December 2018), do not require specific computing infrastructure and provide basic screening functionality for systematic reviews. Key properties of each software tool were identified using a feature analysis adapted for this purpose. This analysis included a weighting developed by a group of medical researchers, therefore prioritising the most relevant features. The highest scoring tools from the feature analysis were then included in a user survey, in which we further investigated the suitability of the tools for supporting T&Ab screening amongst systematic reviewers working in medical research. Results Fifteen tools met our inclusion criteria. They vary significantly in relation to cost, scope and intended user community. Six of the identified tools (Abstrackr, Colandr, Covidence, DRAGON, EPPI-Reviewer and Rayyan) scored higher than 75% in the feature analysis and were included in the user survey. Of these, Covidence and Rayyan were the most popular with the survey respondents. Their usability scored highly across a range of metrics, with all surveyed researchers (n = 6) stating that they would be likely (or very likely) to use these tools in the future. Conclusions Based on this study, we would recommend Covidence and Rayyan to systematic reviewers looking for suitable and easy to use tools to support T&Ab screening within healthcare research. These two tools consistently demonstrated good alignment with user requirements. We acknowledge, however, the role of some of the other tools we considered in providing more specialist features that may be of great importance to many researchers.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: found
            Is Open Access

            ARTS: autonomous research topic selection system using word embeddings and network analysis

            The materials science research process has become increasingly autonomous due to the remarkable progress in artificial intelligence. However, autonomous research topic selection (ARTS) has not yet been fully explored due to the difficulty of estimating its promise and the lack of previous research. This paper introduces an ARTS system that autonomously selects potential research topics that are likely to reveal new scientific facts yet have not been the subject of much previous research by analyzing vast numbers of articles. Potential research topics are selected by analyzing the difference between two research concept networks constructed from research information in articles: one that represents the promise of research topics and is constructed from word embeddings, and one that represents known facts and past research activities and is constructed from statistical information on the appearance patterns of research concepts. The ARTS system is also equipped with functions to search and visualize information about selected research topics to assist in the final determination of a research topic by a scientist. We developed the ARTS system using approximately 100 00 articles published in the Computational Materials Science journal. The results of our evaluation demonstrated that research topics studied after 2016 could be generated autonomously from an analysis of the articles published before 2015. This suggests that potential research topics can be effectively selected by using the ARTS system.
              Bookmark
              • Record: found
              • Abstract: not found
              • Article: not found

              Authorship policy of the Korean journal of radiology regarding artificial intelligence large language models such as ChatGTP

                Bookmark

                Author and article information

                Journal
                angiologia
                Angiología
                Angiología
                Arán Ediciones S.L. (Madrid, Madrid, Spain )
                0003-3170
                1695-2987
                October 2023
                : 75
                : 5
                : 344-345
                Affiliations
                [2] Concepción Bío-Bío orgnameUniversidad Católica de la Santísima Concepción orgdiv1Facultad de Medicina orgdiv2Departamento de Salud Pública Chile
                [3] Santiago orgnameUniversidad Bernardo O'Higgins orgdiv1Facultad de Ciencias de Salud Chile
                [1] Santiago Santiago de Chile orgnameUniversidad de Las Américas orgdiv1Facultad de Salud y Ciencias Sociales Chile
                [4] Santiago orgnameUniversidad Tecnológica Metropolitana orgdiv1Facultad de Administración y Economía orgdiv2Departamento Gestión de la Información Chile
                Article
                S0003-31702023000500012 S0003-3170(23)07500500012
                10.20960/angiologia.00552
                a093d741-6ec7-4821-8025-01e998e56f16

                This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

                History
                Page count
                Figures: 0, Tables: 0, Equations: 0, References: 7, Pages: 2
                Product

                SciELO Spain

                Categories
                Carta al Director

                Comments

                Comment on this article