A framework for integrating biomedical knowledge in Wikidata with open biological and biomedical ontologies and MeSH keywords.

This study presents a comprehensive framework to enhance Wikidata as an open and collaborative knowledge graph by integrating Open Biological and Biomedical Ontologies (OBO) and Medical Subject Headings (MeSH) keywords from PubMed publications. The primary data sources include OBO ontologies and MeSH keywords, which were collected and classified using SPARQL queries for RDF knowledge graphs. The semantic alignment between OBO ontologies and Wikidata was evaluated, revealing significant gaps and distorted representations that necessitate both automated and manual interventions for improvement.

MeSH2Matrix: combining MeSH keywords and machine learning for biomedical relation classification based on PubMed.

Biomedical relation classification has been significantly improved by the application of advanced machine learning techniques on the raw texts of scholarly publications. Despite this improvement, the reliance on large chunks of raw text makes these algorithms suffer in terms of generalization, precision, and reliability. The use of the distinctive characteristics of bibliographic metadata can prove effective in achieving better performance for this challenging task.

Pseudotumoral neuro-behcet's disease: case series and review of literature.

Background: Behcet's disease (BD) is a multisystem autoimmune relapsing vasculitis with an almost unknown etiology involving both large and small vessels. The neurological involvement called neuro-Behcet's disease (NBD) is rare. NBD can be responsible for tumor-like masses mimicking low-grade gliomas in only a few cases.

Global visibility of publications through Digital Object Identifiers.

This brief research report analyzes the availability of Digital Object Identifiers (DOIs) worldwide, highlighting the dominance of large publishing houses and the need for unique persistent identifiers to increase the visibility of publications from developing countries. The study reveals that a considerable amount of publications from developing countries are excluded from the global flow of scientific information due to the absence of DOIs, emphasizing the need for alternative publishing models. The authors suggest that the availability of DOIs should receive more attention in scholarly communication and scientometrics, contributing to a necessary debate on DOIs relevant for librarians, publishers, and scientometricians.

Apoplexy in pituitary metastasis revealing a lung carcinoma.

Pituitary metastasis (PM) is an uncommon manifestation of systemic malignant tumours. It is the least common site of intracranial metastases. As PM has no clinical or radiological pathognomonic features, their diagnosis is challenging.

Letter to the Editor: FHIR RDF - Why the world needs structured electronic health records.

This comment discusses the benefits of representing and reusing the information in Electronic Health Record databases as knowledge graphs in the RDF format based on the FHIR RDF specification. As a structured representation of clinical data, FHIR RDF-based electronic health records allow a simpler and more effective integration of biomedical information using semantic alignment, queries, interoperability, and federation to provide better support for health practice and research.

Using logical constraints to validate statistical information about disease outbreaks in collaborative knowledge graphs: the case of COVID-19 epidemiology in Wikidata.

Urgent global research demands real-time dissemination of precise data. Wikidata, a collaborative and openly licensed knowledge graph available in RDF format, provides an ideal forum for exchanging structured data that can be verified and consolidated using validation schemas and bot edits. In this research article, we catalog an automatable task set necessary to assess and validate the portion of Wikidata relating to the COVID-19 epidemiology.

Awakening sleeping beauties during the COVID-19 pandemic influences the citation impact of their references.

In this research letter, we build upon recent studies about the sleeping beauties awakened by the COVID-19 pandemic. We prove that a peak of citations for sleeping beauties is associated with a sharp increase in the number of citations received by their references. This demonstrates the existence of a cascading activation of citation-based sleeping beauties.

Enhancing filter-based parenthetic abbreviation extraction methods.

This letter discusses the limitations of the use of filters to enhance the accuracy of the extraction of parenthetic abbreviations from scholarly publications and proposes the usage of the parentheses level count algorithm to efficiently extract entities between parentheses from raw texts as well as of machine learning-based supervised classification techniques for the identification of biomedical abbreviations to significantly reduce the removal of acronyms including disallowed punctuations.

Wikidata: A large-scale collaborative ontological medical database.

Created in October 2012, Wikidata is a large-scale, human-readable, machine-readable, multilingual, multidisciplinary, centralized, editable, structured, and linked knowledge-base with an increasing diversity of use cases. Here, we raise awareness of the potential use of Wikidata as a useful resource for biomedical data integration and semantic interoperability between biomedical computer systems. We show the data model and characteristics of Wikidata and explain how this database can be automatically processed by users as well as by computer methods and programs.

Computing semantic similarity between biomedical concepts using new information content approach.

The exploitation of heterogeneous clinical sources and healthcare records is fundamental in clinical and translational research. The determination of semantic similarity between word pairs is an important component of text understanding that enables the processing and structuring of textual resources. Some of these measures have been adapted to the biomedical field by incorporating domain information extracted from clinical data or from medical ontologies such as MeSH.