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Skip search results from other journals and go to results- 1182 Journal of Medical Internet Research
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(A) Multicycle superposition of ILI cases at the national level; (B) seasonal variation patterns in the southern region; and (C) seasonal variation patterns in the northern region.
We evaluated the predictive performance of 5 deep learning models—LSTM, N-BEATS, TFT, Ti DE, and transformer—in forecasting ILI positivity rates across national, southern, and northern datasets for weeks 1‐39 of 2024. Model training progress was monitored using fitting visualizations (Figure 2).
J Med Internet Res 2025;27:e74423
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Anonymized raw data could be transferred to an independent statistical team, with group labels withheld (referred to as Group A/B) prior to analysis. Objective indicators would be prioritized, while subjective measures (eg, pain) would undergo third-party blinded assessments, such as remote review of patient diaries by external experts. These steps aim to minimize bias.
J Med Internet Res 2025;27:e71624
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County B, on the east side of the state, is an urban county, with over 370,000 people. The jail had 404 beds and 8300 bookings in 2019. These jails vary in screening methods for suicide risk at jail booking, which reflects variability nationally. County A uses several scripted questions about current and past suicide ideation or attempts, and County B uses several scripted questions and a truncated version of the Columbia Suicide Severity Rating Scale [25].
The 2 jail populations vary demographically.
JMIR Res Protoc 2025;14:e68517
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Our literature search identified a number of m Health interventions, such as B-wise [80], a website with Pr EP information for adolescent girls and young women in South Africa, and Tutu Tester [81], a mobile clinic that used m Health to connect with HIV testers in the community [82,83]; however, these interventions were not included, as their impacts from m Health were not published in peer-reviewed journals or as conference abstracts.
JMIR Mhealth Uhealth 2025;13:e60819
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(B) Co-authorship network Visualization. This panel visualizes the co-authorship network in prone positioning research. Nodes represent authors, and edges between nodes represent co-authorship relationships. The network highlights key authors and their collaboration patterns over time.(C) Network of Co-authors’ Institution Visualization. This panel illustrates the co-authorship network at the institutional level. Nodes represent institutions, and edges between them reflect collaborative publishing efforts.
Interact J Med Res 2025;14:e67276
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