e.g. mhealth
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Skip search results from other journals and go to results- 28 Journal of Medical Internet Research
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Various families of algorithms were employed for data processing to interpret or predict participant status in different studies.
In 1 study, user satisfaction with the app was assessed using a qualitative questionnaire, and all respondents who completed the questionnaire indicated a high level of satisfaction with the app [62]. Overall, the selected studies indicated high feasibility and acceptability of technologies for mental health care.
J Med Internet Res 2025;27:e57418
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Machine learning, a subfield of AI, creates algorithms capable of learning and improving from experience without explicit programming [5,6]. In health care, AI algorithms have been developed to improve medical image analysis, offering benefits such as automatic recognition of abnormalities and disease prediction, ultimately leading to optimized clinical decision-making, cost reduction, and error prevention [7,8].
Interact J Med Res 2025;14:e56240
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The is Main Sleep and TSP algorithms were applied to sequence-level Fitbit data on the Researcher Workbench using the R programming language (R Foundation) [22]. The number of primary versus nonprimary sleep logs identified by the 2 algorithms was evaluated using a 2×2 contingency table.
A data-driven quartile approach was used to empirically examine variation from typical sleep patterns across clinical and demographic characteristics, as well as sleep onset/offset patterns.
J Med Internet Res 2025;27:e71718
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Authors’ Reply: Foundation Models for Generative AI in Time-Series Forecasting
algorithms
J Med Internet Res 2025;27:e79772
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Foundation Models for Generative AI in Time-Series Forecasting
algorithms
J Med Internet Res 2025;27:e76964
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This study aimed to assess the performance of NLP algorithms compared to conventional methods for detecting fall incidence and the mechanism of falls obtained from clinical notes of patients with hip fractures. We hypothesize that NLP algorithms outperform fall ICD codes in detecting falls and their mechanisms in patients with hip fractures.
A retrospective case-control study was conducted, including the data from 4 tertiary hospitals in Greater Boston, Massachusetts.
JMIR Med Inform 2025;13:e66973
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A more detailed technical description of the algorithms and processes is available in Multimedia Appendix 1.
As AI evolves, fully automated synthesis workflows may become feasible, but rigorous validation is essential to ensure trust, transparency, and scientific integrity.
The implementation of new methodologies in the scientific field requires a comparative validation process with established methods to confirm their reliability and effectiveness.
JMIR Form Res 2025;9:e75215
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It is however, for many diseases still unclear whether telemonitoring does lead to more efficient care delivery, as it requires a significant time investment (eg, alert processing, development and implementation of telemonitoring algorithms), generates new data, and needs continuous optimization of clinical workflows [6,7].
Modern telemonitoring platforms are often embedded in existing care paths and include clinical algorithms that triage and process the generated alerts [3,8].
JMIR Med Inform 2025;13:e66066
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TU is primarily a software-driven system engineered to streamline tertiary evidence synthesis, relying on programmed algorithms to automate the majority of its functions. The core of the system is built on a software infrastructure that processes and synthesizes data from SR/MA abstracts stored in MEDLINE. While AI plays a crucial role, particularly through the use of LLMs and machine learning (ML), it is used selectively within the broader software framework to enhance specific tasks.
JMIR Res Protoc 2025;14:e67248
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