ArticleFrontiers in medicine2023
Linguistic and ontological challenges of multiple domains contributing to transformed health ecosystems.
Article in Frontiers in medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed.
- Anatomy-Guided Hybrid CNN-ViT Model with Neuro-Symbolic Reasoning for Early Diagnosis of Thoracic Diseases Multilabel.Diagnostics (Basel, Switzerland) · 2026Article
- A strategic approach to multi-omics literature retrieval in next generation mammalian cell bioprocessing.NPJ systems biology and applications · 2025Review
- Augmented non-hallucinating large language models as medical information curators.NPJ digital medicine · 2024Article
- Unsupervised SapBERT-based bi-encoders for medical concept annotation of clinical narratives with SNOMED CT.Digital healthArticle
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5 authors.
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Abstract
This paper provides an overview of current linguistic and ontological challenges which have to be met in order to provide full support to the transformation of health ecosystems in order to meet precision medicine (5 PM) standards. It highlights both standardization and interoperability aspects regarding formal, controlled representations of clinical and research data, requirements for smart support to produce and encode content in a way that humans and machines can understand and process it. Starting from the current text-centered communication practices in healthcare and biomedical research, it addresses the state of the art in information extraction using natural language processing (NLP). An important aspect of the language-centered perspective of managing health data is the integration of heterogeneous data sources, employing different natural languages and different terminologies. This is where biomedical ontologies, in the sense of formal, interchangeable representations of types of domain entities come into play. The paper discusses the state of the art of biomedical ontologies, addresses their importance for standardization and interoperability and sheds light to current misconceptions and shortcomings. Finally, the paper points out next steps and possible synergies of both the field of NLP and the area of Applied Ontology and Semantic Web to foster data interoperability for 5 PM.
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