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<p>In order for medical systems to decide on the optimal course of treatment, disease prediction is crucial. Ontologies, which have emerged as the most effective method for representing declarative knowledge about symptoms, treatments, and diagnoses, are used to depict these disorders. In this study, an ontology-based technique systematic literature review (SLR) was conducted, taking into account research publications from 2012 to 2025. The SLP was built on certain crucial topics that can progress the field’s research but weren’t taken into account by earlier reviews. This covers the most important diseases in the diagnosis process, the methods of artificial intelligence and ontology utilised, the methods of ontology used, the connections to conventional medicine, the scientific implications of the methods, etc. The review process makes use of the PRISMA process flow mechanism. 45 studies were chosen after the papers underwent quality inspection. Five research questions provided in this paper were answered by the findings. The more prominent diseases considered, A integration and approaches were shown. The overview of significant study trends that highlights the gaps that can pique future researchers’ attention in the medical information system sector is provided in the study’s conclusion.</p>

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Ontology-based medical diagnosis systems: state-of-the-art and future research directions

  • 期刊论文

  • 发表日期：

    2026年6月15日

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  • Abiodun Muyideen Mustapha,
  • Temitope Elizabeth Abioye,
  • Oluwasanya Oyedele,
  • Folasade Mercy Okikiola,
  • Christianah Yetunde Alonge

摘要

In order for medical systems to decide on the optimal course of treatment, disease prediction is crucial. Ontologies, which have emerged as the most effective method for representing declarative knowledge about symptoms, treatments, and diagnoses, are used to depict these disorders. In this study, an ontology-based technique systematic literature review (SLR) was conducted, taking into account research publications from 2012 to 2025. The SLP was built on certain crucial topics that can progress the field’s research but weren’t taken into account by earlier reviews. This covers the most important diseases in the diagnosis process, the methods of artificial intelligence and ontology utilised, the methods of ontology used, the connections to conventional medicine, the scientific implications of the methods, etc. The review process makes use of the PRISMA process flow mechanism. 45 studies were chosen after the papers underwent quality inspection. Five research questions provided in this paper were answered by the findings. The more prominent diseases considered, A integration and approaches were shown. The overview of significant study trends that highlights the gaps that can pique future researchers’ attention in the medical information system sector is provided in the study’s conclusion.