Accelerated evidence synthesis in orthopaedics—the roles of natural language processing, expert annotation and large language models

peer reviewedIn an era of electronical medical records, rapidly expanding publication rates of medical knowledge, and large-scale registries, orthopaedics is in a dire need of innovative approaches to facilitate the adoption of the latest knowledge in clinical practice. While machine learning (ML) has been heralded as one solution to many research tasks hampered by previous technological limitations [12], there is an increasing need to direct our attention towards subdomains of ML that are convenient for the extraction of meaningful clinical information stored in medical records. We believe natural language processing (NLP) to be one such domain of ML, with an immense future potential to catalyse rate-limiting steps in orthopaedic research

Advanced materials foresight: research and innovation indicators related to advanced and smart nanomaterials

Background: Advanced materials are most likely to bring future economic, environmental and social benefits. At the same time, they may pose challenges regarding their safety and sustainability along the entire lifecycle. This needs to be timely addressed by the stakeholders (industry, research, policy, funding and regulatory bodies). As part of a larger foresight project, this study aimed to identify areas of scientific research and technological development related to advanced materials, in particular advanced nanomaterials and the sub-group of smart nanomaterials. The study identified and collected data to build relevant research and innovation indicators and analyse trends, impact and other implications. Methods: This study consisted of an iterative process including a documentation phase followed by the identification, description and development of a set of core research and innovation indicators regarding scientific publications, EU projects and patents. The data was extracted mainly from SCOPUS, CORDIS and PATSTAT databases using a predefined search string that included representative keywords. The trends, distributions and other aspects reflected in the final version of the indicators were analysed, e.g. the number of items in a period of time, geographical distribution, organisations involved, categories of journals, funding programmes, costs and technology areas. Results: Generally, for smart nanomaterials the data used represent around 3.5% of the advanced nanomaterials data, while for each field analysed, they represent 4.4% for publications, 13% for projects and 1.1% for patents. The study shows current trends for advanced nanomaterials at a top-level information that can be further extended with sub-indicators. Generally, the results indicated a significant growth in research into advanced nanomaterials, including smart nanomaterials, in the last decade, leading to an increased availability of information. Conclusion: These indicators identify trends regarding scientific and technological achievements and represent an important element when examining possible impacts on society and policy implications associated to these areas

Chemical information matters: an e-Research perspective on information and data sharing in the chemical sciences

Recently, a number of organisations have called for open access to scientific information and especially to the data obtained from publicly funded research, among which the Royal Society report and the European Commission press release are particularly notable. It has long been accepted that building research on the foundations laid by other scientists is both effective and efficient. Regrettably, some disciplines, chemistry being one, have been slow to recognise the value of sharing and have thus been reluctant to curate their data and information in preparation for exchanging it. The very significant increases in both the volume and the complexity of the datasets produced has encouraged the expansion of e-Research, and stimulated the development of methodologies for managing, organising, and analysing "big data". We review the evolution of cheminformatics, the amalgam of chemistry, computer science, and information technology, and assess the wider e-Science and e-Research perspective. Chemical information does matter, as do matters of communicating data and collaborating with data. For chemistry, unique identifiers, structure representations, and property descriptors are essential to the activities of sharing and exchange. Open science entails the sharing of more than mere facts: for example, the publication of negative outcomes can facilitate better understanding of which synthetic routes to choose, an aspiration of the Dial-a-Molecule Grand Challenge. The protagonists of open notebook science go even further and exchange their thoughts and plans. We consider the concepts of preservation, curation, provenance, discovery, and access in the context of the research lifecycle, and then focus on the role of metadata, particularly the ontologies on which the emerging chemical Semantic Web will depend. Among our conclusions, we present our choice of the "grand challenges" for the preservation and sharing of chemical information

Products and Services

Today’s global economy offers more opportunities, but is also more complex and competitive than ever before. This fact leads to a wide range of research activity in different fields of interest, especially in the so-called high-tech sectors. This book is a result of widespread research and development activity from many researchers worldwide, covering the aspects of development activities in general, as well as various aspects of the practical application of knowledge

The measurement of science and technology in China.

This paper introduced the background about the measurement of science and technology in China and selectively introduced the most recent statistic results released by the Institute of Scientific and Technical Information of China.China; Science and technology; Measurement;

From medical language processing to BioNLP domain

This paper presents the results of a terminological work on a reference corpus in the domain of Biomedicine. In particular, the research tends to analyse the use of certain terms in Biomedicine in order to verify their change over the time with the aim of retrieving from the net the very essence of documentation. The terminological sample contains words used in BioNLP and biomedicine and identifies which terms are passing from scientific publications to the daily press and which are rather reserved to scientific production. The final scope of this work is to determine how scientific dissemination to an ever larger part of the society enables a public of common citizens to approach communication on biomedical research and development; and its main source is a reference corpus made up of three main repositories from which information related to BioNLP and Biomedicine is extracted. The paper is divided in three sections: 1) an introduction dedicated to data extracted from scientific documentation; 2) the second section devoted to methodology and data description; 3) the third part containing a statistical representation of terms extracted from the archive: indexes and concordances allow to reflect on the use of certain terms in this field and give possible keys for having access to the extraction of knowledge in the digital era

Automatic extraction of function-behaviour-state information from patents

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