e.g. mhealth
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Skip search results from other journals and go to results- 26 Journal of Medical Internet Research
- 15 JMIR Medical Education
- 9 JMIR Medical Informatics
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Women in medicine face significant barriers to compensation, career advancement, and research support, even when controlling for specialty, age, and/or clinical experience [1]. These barriers are especially pronounced in cardiology, where women comprise only 15% of practicing cardiologists and are less likely to be clinical trial leaders or present late-breaking trials at major cardiovascular conferences [2-4].
JMIR Cardio 2025;9:e66308
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In doing so, the article puts an emphasis on the social and legal conceptualizations of trust and their implications for trustworthy AI in medicine.
While there is a plethora of literature on trust and trustworthiness of AI [15,16,27] and in medicine in particular [11,28-30], a deeper conceptualization of the terms used is needed for specific practices in medicine and health care.
J Med Internet Res 2025;27:e71236
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The application of artificial intelligence in the field of medicine has a long history, dating back to the mid-20th century. Initially used in research, its use in clinical medicine emerged in the 1970s. The MYCIN computer expert system was used at Stanford University for the purpose of diagnosing and treating infectious diseases with antibiotics [1]. Even though the diagnoses produced by the system at that time exhibited remarkably high success rates, it was not accepted at that time.
JMIR Form Res 2025;9:e63857
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Nevertheless, it is not specialized in medicine, and numerous websites present medical-related information without being reviewed by scientists or physicians [20,21], often leading to low-quality information [22]. Consequently, physicians must carefully evaluate the quality of information obtained from websites. Furthermore, physicians and medical students often prefer using Google over medicine-specific databases to answer clinical questions [23].
JMIR Form Res 2025;9:e62754
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Despite the dangers and increasing rates of online medicine purchases, there has been a scarcity of research to examine online medicine purchasing behavior. This paper examined online medicine purchasing through a behavioral model. The theory of planned behavior literature describes that past behavior, attitudes, perceived behavioral control (PBC), and norms affect a consumer’s intention and that this intention leads to a behavior.
JMIR Form Res 2025;9:e55391
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Digital Representation of Patients as Medical Digital Twins: Data-Centric Viewpoint
Much has been published about digital twins as a landmark of the digital transition of medicine and as a technology to address the uniqueness of patients in a precision medicine framework [1]. The digital twin concept combines engineering technologies attempting to represent objects digitally while maintaining a continuous connection with the physical object in the real world [2].
JMIR Med Inform 2025;13:e53542
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There are few prominent medicine-based national career development programs in the United States targeted to women, such as the Association of American Medical Colleges (AAMC) Early-Career and Mid-Career programs, the Hedwig van Ameringen Executive Leadership in Academic Medicine (ELAM) program, the University of Michigan’s Rudi Ansbacher Advancing Women in Academic Medicine Leadership Scholars Program, and Harvard’s Career Advancement and Leadership Skills for Women, with metrics demonstrating postparticipation
JMIR Form Res 2025;9:e65561
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Creating an ADR post classification model based on medical terminology from databases such as Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT) or The Medical Dictionary for Regulatory Activities (Med DRA) creates a clinical foundation for future applications and can be used for various drugs and ADRs.
Using Chinese social media posts as the original dataset, we proposed a semisupervised learning framework for detecting Chinese drug terms and ADR terms [8].
JMIR Med Inform 2024;12:e45289
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Task-Specific Transformer-Based Language Models in Health Care: Scoping Review
Similarly, Locke et al [7] provided a comprehensive overview of NLP in medicine, emphasizing the potential of NLP technologies in transforming medical practice. Adyashreem et al [8] surveyed various NLP techniques in the biomedical field, shedding light on how these techniques can be applied to biomedical text for improved information extraction and analysis.
JMIR Med Inform 2024;12:e49724
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Prompt Engineering Paradigms for Medical Applications: Scoping Review
Reference 7: Large language models in medicine Case study in medicine Reference 29: Performance of ChatGPT incorporated chain-of-thought method in bilingual nuclear medicine 35: Diagnostic reasoning prompts reveal the potential for large language model interpretability in medicine Reference 108: MED-Prompt: a novel prompt engineering framework for medicine prediction on free-textmedicine
J Med Internet Res 2024;26:e60501
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