e.g. mhealth
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- 27 Journal of Medical Internet Research
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Furthermore, studies on excessive crying are often small in scale, and an integrative care framework for parents with excessively crying infants is lacking.
To optimally identify the needs of parents with excessively crying infants, it is crucial to assess both their current experiences and their perceptions of an ideal support situation.
JMIR Pediatr Parent 2025;8:e75669
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This paper aims to provide a framework for the creation of microintervention systems and the narratives served by these through their microinterventions. This framework is intended to be an evidence-based conceptual framework for classifying, designing, and studying microinterventions in digital health technologies that address different health conditions. The framework is useful for designers and researchers wishing to build or study microintervention systems.
J Med Internet Res 2025;27:e72658
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To address these challenges, this study aims to develop an interpretable framework that dynamically aligns patient subgroups with optimized classifier selection.
JMIR Med Inform 2025;13:e63581
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The framework suggests using standards, but no IGs or interoperability profiles are provided.
Yusoff et al [23] developed a conceptual framework for serious learning games. It combines learning and pedagogy theory with gaming requirements.
JMIR Serious Games 2025;13:e69246
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To achieve the aim of the study, there are four specific objectives:
Identify governance requirements for AI applications in health care delivery organizations
Examine existing AI governance processes and current best practices for AI governance
Codevelop an AI governance framework to meet the needs of health care organizations
Test and refine the AI governance framework by applying it to exemplar AI tools
We will produce a comprehensive AI governance framework for a health care delivery organization.
JMIR Res Protoc 2025;14:e75702
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A scoping review conducted in 2023 examined EPAs within the broader framework of dental education. The review primarily focused on the development of EPAs for undergraduate and postgraduate dental students, as well as the evaluation of EPAs in general dentistry, without addressing the perspectives of dental educators [11]. This proposed scoping review aims to specifically focus on the literature related to EPAs for dental educators.
JMIR Res Protoc 2025;14:e74225
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The objective of this study was to generate a systematic comparative analysis of the FTSS assessment framework for health apps with the 82304‐2 framework, to identify all new and relevant concepts distinct to 82304‐2 and all Catalonia-specific concepts addressed by the FTSS framework, and to adequately consider and allow proper integration of 82304‐2 in Catalonia.
JMIR Mhealth Uhealth 2025;13:e67858
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Accordingly, we formulated an ML-based framework to identify participants using the clinical laboratory test values of candidates. In this study, we chose to compare the ML-based method with a random selection method, which we considered representative of the common practice in clinical settings where patient lists are screened sequentially.
JMIR AI 2025;4:e64845
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From the 2 frameworks uncovered, one framework was incomplete, while the other framework was brief and focused on ophthalmology [34]. The ophthalmology curriculum framework lacks adaptability, as it may prove inadequate for family medicine residency due to the diverse, community-based nature of family medicine, which differs significantly from the highly technological and hospital-based focus of ophthalmology.
JMIR Med Educ 2025;11:e66828
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Guideline-Incorporated Large Language Model-Driven Evaluation of Medical Records Using MedCheckLLM
In this study, we introduce a framework that consists of a multistep approach for medical record evaluation that incorporates guidelines into the evaluation process (ie, guideline-in-the-loop). Our proposed algorithm, Med Check LLM, is an LLM-driven, structured reasoning mechanism designed to automate the evaluation of medical records against evidence-based guidelines. The guidelines are deterministically accessed and returned to the LLM as input without further model fine-tuning.
JMIR Form Res 2025;9:e53335
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