e.g. mhealth
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Skip search results from other journals and go to results- 38 JMIR Medical Informatics
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Furthermore, with regard to function, it is important for clinicians and patients to understand the limits of these predictions, including the data used for training the algorithm and the implications for both accepting and rejecting the output [84]. Unfortunately, the lack of algorithmic transparency is a common finding.
J Med Internet Res 2025;27:e58723
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Striking a Balance: Innovation, Equity, and Consistency in AI Health Technologies
In the United States, the product type can vary from a device software or algorithm that may be classified as mobile medical apps, software functions that are not medical devices, clinical decision support software, or software as a medical device (Sa MD) [24-26]. Each of these product types needs different types and levels of evidence to support them in the market and may need regulatory approval.
JMIR AI 2025;4:e57421
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Are Dating App Algorithms Making Men Lonely and Does This Present a Public Health Concern?
algorithm
JMIR Form Res 2025;9:e70594
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The purpose of this study was to develop an algorithm using ML techniques to forecast whether the initial vancomycin regimen to be administered can achieve an AUC24/MIC ratio within the therapeutic range. In other words, the final output of the ML algorithm predicted “yes” or “no” based on whether the AUC24/MIC of vancomycin falls within the therapeutic range of 400 to 600.
J Med Internet Res 2025;27:e63983
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The algorithm takes as input the 3 D ultrasound image and outputs the corresponding predicted segmentation. During development, the algorithm learned to set its internal parameters by minimizing the difference between the predicted segmentation and the segmentations obtained in VR. Two separate models were developed: one for segmenting the embryo and another for the embryonic head.
J Med Internet Res 2025;27:e60887
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