e.g. mhealth
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Guideline-Incorporated Large Language Model-Driven Evaluation of Medical Records Using MedCheckLLM
The primary objective of this research is to introduce the conceptual framework and assess its feasibility.
The Med Check LLM algorithm begins by extracting a patient’s diagnosis from the medical report (Figure 1). Based on the diagnosis, it suggests an appropriate guideline. A human medical expert makes the final guideline selection. Guidelines are then accessed independently of the LLM’s mechanisms using programmatically built interfaces for guideline retrieval.
JMIR Form Res 2025;9:e53335
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Toward a New Conceptual Framework for Digital Mental Health Technologies: Scoping Review
Based on the findings of the literature review and reflections from the working group, we developed a conceptual framework for DMHTs. The conceptual framework includes 8 domains that represent the characteristics of DMHTs (Figure 2). They each represent important characteristics of DMHTs that are likely to influence the benefits they can deliver for individuals and the wider system and risks that will need to be mitigated during use.
Domains included within a new conceptual framework.
JMIR Ment Health 2025;12:e63484
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Digital Representation of Patients as Medical Digital Twins: Data-Centric Viewpoint
conceptual conceptual clarification
JMIR Med Inform 2025;13:e53542
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Much of the care delivered for children with medical complexity occurs in the home managed by the primary caregivers and can be framed by the conceptual terms of self-management or, more broadly, family management [4,8].
JMIR Form Res 2023;7:e52454
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In the concluding stage, there will be explicit between-methods triangulation of the findings of the respective methodological approaches (qualitative description using directed content analysis and conventional content analysis and document analysis) used in stages 1 and 2 to develop a final conceptual framework [58,59].
JMIR Res Protoc 2023;12:e50137
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