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An Ontology for Digital Medicine Outcomes: Development of the Digital Medicine Outcomes Value Set (DOVeS)

An Ontology for Digital Medicine Outcomes: Development of the Digital Medicine Outcomes Value Set (DOVeS)

The taxonomy resided in a spreadsheet, but without the functionalities of an ontology. A number of Ontology Engineering Methodologies (OEMs) exist to guide and structure ontology development from a state of informal knowledge to formal representation [16]. Many OEMs have been organized into different classes, including, for example, collaborative, noncollaborative, and custom OEMs [17].

Benjamin Rosner, Matthew Horridge, Guillen Austria, Tiffany Lee, Andrew Auerbach

JMIR Med Inform 2025;13:e67589

Semiology Extraction and Machine Learning–Based Classification of Electronic Health Records for Patients With Epilepsy: Retrospective Analysis

Semiology Extraction and Machine Learning–Based Classification of Electronic Health Records for Patients With Epilepsy: Retrospective Analysis

We defined the scope of this domain of ontology as epileptic semiology by reference, reused the more authoritative epilepsy-related ontologies and terminology sets as standard terminology, referred to the basic formalized ontology (BFO) as the top-level ontology, and hierarchically arranged the entities according to their domain-neutral framework.

Yilin Xia, Mengqiao He, Sijia Basang, Leihao Sha, Zijie Huang, Ling Jin, Yifei Duan, Yusha Tang, Hua Li, Wanlin Lai, Lei Chen

JMIR Med Inform 2024;12:e57727

Bridging Data Models in Health Care With a Novel Intermediate Query Format for Feasibility Queries: Mixed Methods Study

Bridging Data Models in Health Care With a Novel Intermediate Query Format for Feasibility Queries: Mixed Methods Study

The criteria content and the required reintroduction of data model—dependent information are obtained from an automatically generated search ontology [36]. While the expression of eligibility criteria within a specific data model context is well established and adequately discussed in this work, research on a data-agnostic intermediate format for computable eligibility has been sparse in recent years.

Lorenz Rosenau, Julian Gruendner, Alexander Kiel, Thomas Köhler, Bastian Schaffer, Raphael W Majeed

JMIR Med Inform 2024;12:e58541

Use of SNOMED CT in Large Language Models: Scoping Review

Use of SNOMED CT in Large Language Models: Scoping Review

The UMLS serves as a thesaurus for biomedical terminology systems such as the Medical Subject Headings, International Classification of Diseases, Gene Ontology, Human Phenotype Ontology, and SNOMED CT, all curated and managed by the United States National Library of Medicine.

Eunsuk Chang, Sumi Sung

JMIR Med Inform 2024;12:e62924

An Ontology to Bridge the Clinical Management of Patients and Public Health Responses for Strengthening Infectious Disease Surveillance: Design Science Study

An Ontology to Bridge the Clinical Management of Patients and Public Health Responses for Strengthening Infectious Disease Surveillance: Design Science Study

As requirements for the ontology to achieve the intended goals, we formulated the competency questions (CQs) described in Table 1. CQs specify functional requirements for an ontology and are used to evaluate whether the ontology fulfills the elicited requirements [38]. The use of CQs has been proposed in several ontology engineering methodologies such as the Tropos methodology [39] and the Ne On Methodology framework [40].

Sachiko Lim, Paul Johannesson

JMIR Form Res 2024;8:e53711

Artificial Intelligence–Augmented Clinical Decision Support Systems for Pregnancy Care: Systematic Review

Artificial Intelligence–Augmented Clinical Decision Support Systems for Pregnancy Care: Systematic Review

Among these studies, forms of knowledge base include Arden syntax and ontology that have been widely used for formal representation of clinical guidelines and graph-based medical knowledge, as well as XML as a markdown language for web and mobile-based CDSS applications. Specifically, in support of diagnostics and therapeutics recommendations for ectopic pregnancy, ontology has been used for supporting the annotation of medical images (eg, ultrasound images for obstetrics) [26,27].

Xinnian Lin, Chen Liang, Jihong Liu, Tianchu Lyu, Nadia Ghumman, Berry Campbell

J Med Internet Res 2024;26:e54737

Electronic Health Record–Oriented Knowledge Graph System for Collaborative Clinical Decision Support Using Multicenter Fragmented Medical Data: Design and Application Study

Electronic Health Record–Oriented Knowledge Graph System for Collaborative Clinical Decision Support Using Multicenter Fragmented Medical Data: Design and Application Study

Xiao et al [15] used Ontology-Based Data Access to establish a virtual fast health care interoperability resources–based knowledge graph derived from Observational Medical Outcomes Partnership (OMOP) EHR data. This approach facilitates data interoperability with exceptional efficiency and generality. Although these studies greatly enhance data interoperability, they do not incorporate decision support functions. 3.

Yong Shang, Yu Tian, Kewei Lyu, Tianshu Zhou, Ping Zhang, Jianghua Chen, Jingsong Li

J Med Internet Res 2024;26:e54263

Dermoscopy Differential Diagnosis Explorer (D3X) Ontology to Aggregate and Link Dermoscopic Patterns to Differential Diagnoses: Development and Usability Study

Dermoscopy Differential Diagnosis Explorer (D3X) Ontology to Aggregate and Link Dermoscopic Patterns to Differential Diagnoses: Development and Usability Study

The information artifact ontology (IAO) [31] is part of the open biological and biomedical ontology (OBO) foundry. IAO represents a general abstraction of informational objects (like documents and components within those documents—eg, figures, images). Like many OBO foundry ontologies, IAO uses the basic formal ontology and relation ontology as part of its architecture model. We minimally reused some of the term entities and properties like IAO:image and “denoted by.”

Rebecca Z Lin, Muhammad Tuan Amith, Cynthia X Wang, John Strickley, Cui Tao

JMIR Med Inform 2024;12:e49613

Semantic Interoperability of Electronic Health Records: Systematic Review of Alternative Approaches for Enhancing Patient Information Availability

Semantic Interoperability of Electronic Health Records: Systematic Review of Alternative Approaches for Enhancing Patient Information Availability

Search terms: (((((EHR) OR (EMR)) OR (“Electronic Health Record”)) OR (“Electronic Medical Record”)) AND (((((“Semantic interoperability”) OR ((“data model”) AND (“Semantic interoperability”))) OR ((((“classification”) OR (ontology)) OR (terminology)) AND (“Semantic interoperability”))) OR (((“data content”) OR (“data format”)) AND (“Semantic interoperability”))) OR ((“Semantic interoperability”) AND (standard))) Filters used: abstract, full text, and English The research team first screened all the remaining

Sari Palojoki, Lasse Lehtonen, Riikka Vuokko

JMIR Med Inform 2024;12:e53535

A Semantic Approach to Describe Social and Economic Characteristics That Impact Health Outcomes (Social Determinants of Health): Ontology Development Study

A Semantic Approach to Describe Social and Economic Characteristics That Impact Health Outcomes (Social Determinants of Health): Ontology Development Study

Some impactful examples of ontologies include the Systematized Nomenclature of Medicine–Clinical Terms [6] and Gene Ontology [7], which are hosted on the National Center for Biomedical Ontology [8] and the OBO Foundry [9]; for example, the National Center for Biomedical Ontology Bio Portal is an open repository of >700 biomedical ontologies [8], whereas the OBO Foundry hosts interoperable biomedical and health ontologies that share a common framework [9].

Daniela Dally, Muhammad Amith, Rebecca L Mauldin, Latisha Thomas, Yifang Dang, Cui Tao

Online J Public Health Inform 2024;16:e52845