e.g. mhealth
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Skip search results from other journals and go to results- 6 JMIR Medical Informatics
- 4 Journal of Medical Internet Research
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The proposed system uses structured EHR data following the Observational Medical Outcomes Partnership (OMOP) common data model (CDM) for semantic reasoning and clinical applications [33]. The semantic organization of EHR data within the knowledge graph adheres to the structure outlined in the OMOP CDM.
J Med Internet Res 2024;26:e54263
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The scope of the review was semantic interoperability, that is, organizational, legal, and technical interoperability were excluded [7]. Semantic interoperability was apprehended based on the European Interoperability Framework (EIF) that provides a common set of principles and guidance for the design and development of interoperable digital services. In the EIF, semantic interoperability covers both semantic and syntactic aspects.
JMIR Med Inform 2024;12:e53535
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Semantic research approaches and related studies.
The distribution of the 6 semantic approaches is as follow: mapping (31/126, 24.6%), RDF or OWL (24/126, 19%), ML and NLP (20/126, 15.9%), annotation (18/126, 14.3%), terminology (18/126, 14.3%), and ontology (15/126, 11.9%).
The selected studies used at least one of the 6 identified semantic research approaches, and most studies used more than one research approach.
J Med Internet Res 2024;26:e45209
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The Necessity of Interoperability to Uncover the Full Potential of Digital Health Devices
This combines the syntactic interoperability (structure and data format) enabled by standards such as FHIR with the semantic interoperability enabled by health terminologies. The Systematized Nomenclature of Medical Clinical Terms (SNOMED CT) is currently the most appropriate and comprehensive clinical health terminology with natural language properties [14,15].
JMIR Med Inform 2023;11:e49301
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These approaches represent an advancement toward better semantic interoperability to support public health surveillance [14], greatly reducing the burden of reporting from clinical providers and improving the completeness and timeliness of those reports [15]. However, further evaluation and consideration is required to achieve a greater level of success and widespread implementation.
JMIR Public Health Surveill 2023;9:e38868
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Cognitive tests incorporated in the Preclinical Alzheimer’s Cognitive Composite with semantic processing (PACC5) were administered. Tests were manually scored, and a mean Z-score was calculated as described previously [11].
JMIR Aging 2022;5(3):e37090
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Predicting Health Material Accessibility: Development of Machine Learning Algorithms
For health education texts, the cognitive difficulty in understanding medical information is caused not only by medical jargon and complex sentences but also by semantic meanings, which cannot be directly represented by word and sentence length alone [15-17]. However, readability estimation tools considering semantic features are few and underexplored.
JMIR Med Inform 2021;9(9):e29175
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This suggests that, at the level of self-reported obsessional thoughts, most obsessions have close semantic links with each other. Thus, although unique obsessions are protean, many examples, even across cluster subtypes, may actually have underlying latent relationships with each other.
J Med Internet Res 2021;23(6):e25482
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To precisely represent phenotype knowledge in clinical guidelines, it is necessary to introduce fine-grained semantic information models [11], which consider phenotypes and attributes simultaneously. The currently available semantic models for representing phenotype information include but are not limited to clinical element models (CEMs) [12], the Health Level Seven fast health care interoperability resource (FHIR) model [13], and the clinical quality language model [14].
J Med Internet Res 2021;23(6):e26892
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