e.g. mhealth
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Skip search results from other journals and go to results- 2372 Journal of Medical Internet Research
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Students’ Perceptions of Learning Analytics for Mental Health Support: Qualitative Study
Many students identified artificial intelligence (AI) as a potential solution for tracking students’ mental health and implementing timely interventions with minimal effort from academic staff. For example, they suggested that algorithms adjusted to individual differences could offer personalized recommendations to maximize mental health. However, some participants expressed skepticism about the accuracy of these automated systems and that they would be overly intrusive in their lives.
JMIR Form Res 2025;9:e70327
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These robots integrate artificial intelligence (AI) and natural language processing to a certain extent, enabling them to interact more naturally with users, leading to enhanced engagement and adaptation to different social contexts [7]. Within geriatric institutions, SARs have the potential to alleviate caregiver workloads, provide cognitive and social stimulation for patients, and assist with daily tasks [8].
JMIR Hum Factors 2025;12:e76496
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Artificial Intelligence in Health Promotion and Disease Reduction: Rapid Review
Recent advancements in artificial intelligence (AI) can be widely used in the medical field to improve patient care [19] and can also be effective in encouraging healthy behaviors and lifestyle changes [20]. AI, as a branch of computer science, simulates human cognition to perform tasks such as reasoning, learning, and decision-making [21,22].
J Med Internet Res 2025;27:e70381
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Reference 9: Remote evaluation of Parkinson’s disease using a conventional webcam and artificial intelligence
J Med Internet Res 2025;27:e67986
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AI: artificial intelligence; CPA: conventional physical activity; Mr.PT: Mixed Reality–Based Physical Therapy.
Table 1 shows the demographic characteristics of the participants. Each participant completed all experimental tasks and exercises. The CPA and Mr.PT groups did not differ significantly in terms of sex, age, height, weight, or BMI (P>.05).
Participants’ demographic characteristics (N=30).
a Mr.PT: Mixed Reality–Based Physical Therapy.
b CPA: conventional physical activity.
JMIR Serious Games 2025;13:e76357
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Preliminary qualitative analysis suggests three recurring themes: (1) interface anxiety, (2) family-mediated use, and (3) trust in artificial intelligence (AI)–driven systems. First, participants reported anxiety when confronted with unfamiliar buttons, icons, or English terminology. They often deferred to family members or care workers to handle advanced features. Second, many older adults rely on adult children or relatives to set up smartphones, download health apps, and troubleshoot technical issues.
JMIR Res Protoc 2025;14:e63094
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AI Scribes in Health Care: Balancing Transformative Potential With Responsible Integration
In response, ambient artificial intelligence (AI) scribes have emerged as promising transformative technologies. These technologies aim to listen to patient-practitioner conversations during clinic visits or other synchronous encounters; then, they generate clinical notes for health care practitioner review, revision, and approval.
JMIR Med Inform 2025;13:e80898
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In response to these challenges, artificial intelligence (AI) has emerged as a promising tool in medical education [25-28]. Until recent breakthroughs, AI performance remained inadequate due to technical limitations [29]. However, the current development of suitable technologies, including Compute Unified Device Architecture and advanced graphics processing units, has remarkably enhanced AI capabilities [30-33].
JMIR Med Educ 2025;11:e77332
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Consumer Data is Key to Artificial Intelligence Value: Welcome to the Health Care Future
Artificial intelligence (AI), particularly large language models (LLMs), holds extraordinary promise in unlocking and interpreting vast volumes of data for public and professional use. Of the projected 180 Zettabytes [1] of global data to be collected by 2025, less than 1% is ever tagged or analyzed [2]. Without the aid of AI, the sheer volume of data exceeds human capacity to meaningfully use this valuable collection.
J Particip Med 2025;17:e68261
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The current growth in artificial intelligence (AI) applications, including predictive analytics and personalized medicine systems to multimodal diagnostic decision-support systems, has revealed requirements for data and the underlying data management architectures [4].
J Med Internet Res 2025;27:e74976
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