SynthesisFrontiers in artificial intelligence2026
Enhancing healthcare through ontology: a systematic review of challenges and future directions.
Synthesis in Frontiers in artificial intelligence, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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0 citing papers in PubMed.
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Authors and funding
2 authors.
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Abstract
This study explores the role of ontology in healthcare by surveying numerous research articles to provide a comprehensive overview of its applications, benefits, and challenges. Ontologies, which enable structured representation and integration of complex healthcare knowledge, have been increasingly employed to enhance data interoperability, improve clinical decision making, and support personalized medicine. Despite their potential, the development and implementation of ontologies in healthcare face challenges, including issues with data consistency, interoperability across systems, and adaptation to rapidly evolving medical knowledge. Using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) model, we systematically identified, screened, and reviewed relevant studies. This model enabled a rigorous process for article selection, ensuring inclusion of high-quality research that addressed key themes in ontology-based healthcare systems. The survey identifies prevalent issues, such as limited standardization, difficulty in updating ontologies to reflect the latest medical insights, and obstacles in integrating heterogeneous datasets. Additionally, gaps are noted in addressing patient privacy and ethical concerns, which are crucial in healthcare applications. This review contributes by highlighting these challenges and proposing areas for further research, such as developing adaptable, scalable ontologies that are ethically aligned and capable of supporting advanced technologies like AI. The findings underscore the need for collaborative efforts among healthcare providers, data scientists, and policymakers to build robust ontology frameworks that can sustainably support healthcare advancements.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.