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Skip search results from other journals and go to results- 596 Journal of Medical Internet Research
- 207 JMIR Public Health and Surveillance
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Acoustic Features for Identifying Suicide Risk in Crisis Hotline Callers: Machine Learning Approach
Now these acoustic changes can be well captured using acoustic speech features [11]. Moreover, with the development of artificial intelligence technologies such as machine learning, it is possible to analyze highly complex patterns in acoustic features [12]. Using artificial intelligence to automatically analyze features can help us move from a clinical practice model that relies solely on clinician judgment to an evidence-based medicine model based on data measurements [13].
J Med Internet Res 2025;27:e67772
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Follow-up initial usability testing with focus groups that evaluated the digital tools suggested that mobile apps and websites can be designed to increase interest in participating in clinical trials.
A total of 351 respondents participated in the intercept study. The sample was 63.9% (223/351) female.
J Med Internet Res 2025;27:e70852
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Importantly, conditional inference trees can highlight potential statistical predictors for between-group differences (eg, poverty as an additional intersectional factor for younger individuals experiencing SI). This is advantageous for intersectionality research, because our goal is not only to uncover subgroups that explain the heterogeneity in STBs but also to understand the factors associated with the heterogeneity.
J Med Internet Res 2025;27:e65452
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Yet, existing findings suggest uptake and engagement with m Health apps can vary dramatically [5,15]. Moreover, data on the efficacy, acceptability, and utilization of distinct app features is often lacking, thereby limiting our ability to understand what works for whom, when, and under what settings; importantly, this also limits our understanding of which groups of individuals are missed by unique m Health strategies [16-18].
JMIR Mhealth Uhealth 2025;13:e54753
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Another burgeoning branch, sentiment analysis tools, can be used for public opinion analysis, such as epidemic trends [20], willingness for vaccination [10], and even presidential elections [21]. Since the emergence of Chat Generative Pretrained Transformer (Chat GPT), it has also been applied to social media research, such as popular hashtag generation algorithms [22] and the construction of lexica for online pharmacovigilance [23].
JMIR Infodemiology 2025;5:e55065
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TM can be classified based on the communication method (text, video, or audio), communication time (synchronous or asynchronous), the purpose of the consultation (initial consultation or follow-up consultation), and participants in the remote consultation (patient-to-doctor, caregiver-to-doctor, doctor-to-doctor, or health care worker-to-doctor) [14].
In chronic disease management, particularly diabetes, the integration of TM technology with medical professionals has yielded remarkable results [15].
J Med Internet Res 2025;27:e59579
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Factors Influencing Information Distortion in Electronic Nursing Records: Qualitative Study
Specific work habits can contribute to information distortion. Many nurses use the copy-and-paste function to enhance work efficiency. Some nurses prefer to copy records from the previous shifts then adjust them after completing their nursing activities. However, this habit can lead to forgetting to make the necessary adjustments, resulting in identical records across shifts. Additionally, when nurses do not take the time to review their records, errors may go unnoticed.
J Med Internet Res 2025;27:e66959
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Digital Decision Support for Perioperative Care of Patients With Type 2 Diabetes: A Call to Action
It can result in severe metabolic and organ dysfunction, exacerbate organ damage, trigger various disorders, increase infection risk, and even lead to postoperative death [5]. Although optimal glycemic control significantly improves postoperative outcomes in patients with diabetes, particularly in mitigating the risk of infection [6], there have long been obstacles regarding achieving the ideal method for managing blood glucose levels.
JMIR Diabetes 2025;10:e70475
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Therefore, the TTF model can serve as a precursor factor influencing perceived ease of use. Based on this rationale, this study selected the core variable of “perceived ease of use” from the TAM.
Given the complexity and constant evolution of AI, it has yet to become a cornerstone of the health care system or medical education.
J Med Internet Res 2025;27:e62732
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