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The repository aims to create an overview and comparison of software used for systematically screening large amounts of textual data using machine learning.
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The theoretical positioning of a review is of the utmost importance in terms of its contribution to knowledge. This paper clarifies the significance of this design principle for different types of review i.e. for describing, understanding, explaining or testing purposes. Furthermore, new tools now mean that it is both possible and relevant for bibliometrics novices to use bibliometrics to support literature reviews. Applying the BIBGT method and combining two bibliometric techniques –...
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Whilst the ability of generative AI to produce text in English has been widely covered, the implications of its ability to translate and act as a cultural broker into English have received less att…
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We recently published a novel categorization of studies related to virtual reality (VR) in your journal, European Heart Journal—Digital Health.1 Our categorization is based on the usage of VR devices, where type A studies refer to those in which healthcare providers use VR devices and type B studies refer to those in which patients use them. Using this simple definition, we clarified the study trends and characteristics of the two research directions. In this study, we used a classical...
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AI language learning tools are computer programs or software applications that use artificial intelligence (AI) algorithms to help users learn and improve their skills in a foreign language. These technologies have a lot of benefits, such as the ability to save time and speed up learning, to give students personalized learning experiences, and to help them learn about other cultures. In this study, the scientific literature was looked at to find out the pros, cons, opportunities, and...
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Abstract Artificial intelligence (AI) has acquired notorious relevance in modern computing as it effectively solves complex tasks traditionally done by humans. AI provides methods to represent and infer knowledge, efficiently manipulate texts and learn from vast amount of data. These characteristics are applicable in many activities that human find laborious or repetitive, as is the case of the analysis of scientific literature. Manually preparing and writing a systematic...
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Abstract Evidence reviews are widely used to summarize findings from existing studies and, as such, are an important base for policy analysis. Over the past 50 years, three waves of evidence reviews have emerged: (1) the meta‐analysis wave, (2) the mixed‐methods synthesis wave, and (3) the core components wave. The present article first describes these waves and reflects on the benefits and limitations of each wave in the context of policy analysis....
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With the accelerating growth of the academic corpus, doubling every nine years, machine learning is a promising avenue to make systematic review manageable. Though several notable advancements have already been made, the incorporation of machine learning is less than optimal, still relying on a sequential, staged process designed to accommodate a purely human approach, exemplified by PRISMA. Here, we test a spiral, alternating or oscillating approach, where full-text screening is done...
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Systematic approaches to evidence synthesis can improve the rigour, transparency, and replicability of a traditional literature review. However, these systematic approaches are time and resource intensive. We evaluate the ability of OpenAI’s ChatGPT to undertake two initial stages of evidence syntheses (searching peer-reviewed literature and screening for relevance) and develop a novel collaborative framework to leverage the best of both human and AI intelligence. Using a scoping review of...
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