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Skip search results from other journals and go to results- 657 Journal of Medical Internet Research
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Cell colors indicate values ranging from 0.0 (red) to 0.5 (yellow) to 1.0 (green). Columns 2 and 3 present the results of LLM validation against the gold standard. With known preclassified values of epidemiological characteristics (severity, etc) in synthetic posts, the LLMs’ abilities to classify these characteristics from these posts’ content were assessed. Columns 4 and 5 present the results of comparative intermodel validations.
J Med Internet Res 2025;27:e65226
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The MRI report completed by the radiologist can be seen on the left in green, while a GPT-4o–generated, simplified version of the MRI report can be seen on the right in blue. Readability scores (Flesch Readability Ease Score) and reading grade levels (Flesch-Kincaid Grade Level) were determined for each version of the MRI report. AI: artificial intelligence.
JMIR AI 2025;4:e69654
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The State of Remote Patient Monitoring for Chronic Disease Management in the United States
J Med Internet Res 2025;27:e70422
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development (R)
Acquisition of external graphics designer (G)
Selection of software and metrics (J)
Learning to work with existing technologies for scheduling and publishing (AF)
Sudden unexpected team member change (U)
Outputs
Extracting key teaching points from top PECARN articles into tweet (X)
Tweet frequency established at the same time each week (3 times per week) (AH)
Tweet visual structure: Intentional or strategic polls, emojis, bullet points, and multimedia such as images and videos (AA, AB, AC, C,
JMIR Form Res 2025;9:e59481
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The Rapid Online Cognitive Assessment for the Detection of Neurocognitive Disorder: Open-Label Study
We first evaluated how Ro CA evaluated patient drawings (Figure 3 A-C). Ro CA classified 97% (44/46) of the cubes correctly, 91% (42/46) of the infinities correctly, and 98% (45/46) of the clocks correctly. We next calculated the accuracy of Ro CA for each drawing individually (Figure 3 D). We compared the accuracy of each drawing to its statistical baseline by bootstrapping, resampling the accuracy, and counting the number of times it fell below the random classifier.
J Med Internet Res 2025;27:e66735
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