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Textual health records of cancer patients are usually protracted and highly unstructured, making it very time-consuming for health professionals to get a complete overview of the patient's therapeutic course. As such limitations can lead to…
Objectives: Trial registries can be used to measure reporting biases and support systematic reviews but 45% of registrations do not provide a link to the article reporting on the trial. We evaluated the use of document similarity methods to…
The research assessments of countries or institutions should reveal their contribution to the advancement of science. Taking into consideration the correlation that exists between scientific impact and number of citations, research…
Research collaborations, especially long-distance and cross-border collaborations, have become increasingly prevalent worldwide. Recent studies highlighted the significant role of research leadership in collaborations. However, existing…
The rapid rise of international collaboration over the past three decades, demonstrated in coauthorship of scientific articles, raises the question of whether countries benefit from cooperative science and how this might be measured. We…
We analyzed Medical Subject Headings (MeSH) from 21.6 million research articles indexed by PubMed to map this vast space of entities and their relations, providing insights into the origins and future of biomedical convergence. Detailed…
Academic leadership is essential for research innovation and impact. Until now, there has been no dedicated measure of leadership by bibliometrics. Popular bibliometric indices are mainly based on academic output, such as the journal impact…
Governments and organizations design performance-based research funding systems (PBFRS) for strategic aims, such as to selectively allocate scarce resources and stimulate research efficiency. In this work we analyze the relative change in…
Benchmarking, which involves collecting reference datasets and demonstrating method performances, is a requirement for the development of new computational tools, but also becomes a domain of its own to achieve neutral comparisons of…
Exploring whether different patterns emerge across networks generated by organizational structures, co-authorships and citations for characterizing and evaluating cooperative relationships is particularly important for transferring the…
Large Language Models (LLMs) demonstrate remarkable versatility in various NLP tasks but encounter distinct challenges in biomedical due to the complexities of language and data scarcity. This paper investigates LLMs application in the…
Developing high-performing systems for detecting biomedical named entities has major implications. State-of-the-art deep-learning based solutions for entity recognition often require large annotated datasets, which is not available in the…
Named entity recognition has been extensively studied on English news texts. However, the transfer to other domains and languages is still a challenging problem. In this paper, we describe the system with which we participated in the first…
The escalating cost, extended timelines, and low success rates in pharmaceutical research demand a fundamental rethinking of biotechnology R&D infrastructure. This chapter introduces the concept of the AI-Integrated Biotechnology Hub, a…
Biomedical literature is a rapidly expanding field of science and technology. Classification of biomedical texts is an essential part of biomedicine research, especially in the field of biology. This work proposes the fine-tuned DistilBERT,…
A comprehensive bibliometric analysis of the scientific production of Chemical Engineering area has been carried out using the Web of Science database for the period 2000-2011 through three complementary studies. Part 2 demonstrated a…
The Chinese approach to developing a world-class science system includes a vigorous set of programmes to attract back Chinese researchers who have overseas training and work experience. No analysis is available to show the performance of…
The growth rate of the number of scientific publications is constantly increasing, creating important challenges in the identification of valuable research and in various scholarly data management applications, in general. In this context,…
Science and technology systems - and their epistemic communities - are usually hierarchical and composed of a number of strong, large, leading organizations, along with a number of smaller and less influential ones. Moreover, these…
The Large Scale Visual Recognition Challenge based on the well-known Imagenet dataset catalyzed an intense flurry of progress in computer vision. Benchmark tasks have propelled other sub-fields of machine learning forward at an equally…