e.g. mhealth
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Skip search results from other journals and go to results- 21 Journal of Medical Internet Research
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To focus on the most promising approaches while maintaining computational efficiency, we selected 10 datasets corresponding to the top 10 performing models from Experiment 1. This focused approach was selected to specifically examine whether the advantages observed with manual classification could be maintained when transitioning to an automated system; a key consideration for practical implementation.
JMIR Med Inform 2025;13:e65371
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The results, presented in Table 5, clearly demonstrate that the SBERT-Doc SCAN method, when fine-tuned with SBERT, outperforms others in terms of efficiency. Furthermore, within the supervised learning category, the SBERT-MEC model equipped with the DC module surpassed those lacking this module, underlining the value of the DC module in enhancing model performance.
JMIR Form Res 2025;9:e54803
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GPT-3.5 Turbo and GPT-4 Turbo in Title and Abstract Screening for Systematic Reviews
Although more advanced LLMs are expected to outperform previous models in sensitivity, specificity, and efficiency [9], the full impact of model development in citation screening remains to be fully understood.
This study aimed to compare accuracy and efficiency between GPT-3.5 Turbo and GPT-4 Turbo (Open AI)—widely used LLMs in the medical field—in title and abstract screening.
JMIR Med Inform 2025;13:e64682
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Therefore, the use of Bayer’s LLM improved the efficiency of this activity. That must save dozens of hours yearly for our local pharmacovigilance team, which could be dedicated to other activities with higher added value. A unique, short, and reachable training was sufficient to implement the use of My Gen Assist. This consisted of introducing the changes in the tool’s operating mode to the users.
J Med Internet Res 2025;27:e65651
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Therefore, more work is needed to provide stakeholder-led insights into specific barriers to target and facilitators to consider in the early stages of novel technology development, to improve engagement with, and thus the efficacy of, novel digital health technologies aiming to improve the accuracy and efficiency of heart disease diagnosis.
JMIR Cardio 2025;9:e66464
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In response to this growing crisis, one solution researchers have sought to apply is the use of novel health monitoring technologies to tackle the problem of labor shortages in health care systems and to improve productivity and efficiency in care [2-11].
JMIR Hum Factors 2025;12:e59458
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Reference 34: Consistency, efficiency, and scalability in design systems: a comparative analysis of materialefficiency
JMIR Hum Factors 2025;12:e57911
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Automated agitation-sedation evaluation could be an alternative to RASS and play a crucial role in enhancing ICU efficiency, ultimately improving health care outcomes, care quality, and patient safety.
Machine learning aids ICU personnel in the early detection of high-risk events [14]. Previous studies have used ML to predict mortality rates in ICU patients with acute kidney injury, predict postoperative sepsis mortality rates, and forecast extubation failure in the ICU [15-17].
JMIR Med Inform 2025;13:e63601
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Artificial intelligence (AI) is profoundly transforming health care across a range of applications, enhancing both clinical outcomes and operational efficiency. In medical imaging, AI algorithms improve diagnostic accuracy by analyzing complex imaging data, such as from magnetic resonance imaging and computed tomography scans, for highly precise and rapid clinical diagnostics [1].
J Med Internet Res 2025;27:e67485
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