e.g. mhealth
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Skip search results from other journals and go to results- 12 Journal of Medical Internet Research
- 10 JMIR Formative Research
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A Practical Guide and Assessment on Using ChatGPT to Conduct Grounded Theory: Tutorial
Reliability is a key metric for evaluating Chat GPT’s coding performance, assessing whether different coders (human or machine) produce similar results [9-11]. Typical measures include percent agreement (comparing human and artificial intelligence [AI] coding similarity) and the κ coefficient (measuring agreement beyond chance) [12,13].
J Med Internet Res 2025;27:e70122
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Recent studies have extensively evaluated the performance of generative AI models in medical question-answering scenarios. These models have shown promising results in medical licensing examinations [4,5] clinical case discussions and diagnostic reasoning [6,7]. However, their performance varies significantly based on task complexity.
JMIR AI 2025;4:e66796
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The Applications of Large Language Models in Mental Health: Scoping Review
When evaluating the performance of these LLMs, most studies measured the performance of LLMs with various metrics, such as F1-score (54/95, 57%), precision (34/95, 36%), accuracy (45/95, 47%), and recall (32/95, 34%).
The number of studies mapped by country is presented in Figure 3 A (a higher resolution version of figure is also available in Multimedia Appendix 5).
J Med Internet Res 2025;27:e69284
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Thus, in this context it should be considered regarding the corresponding perceived performance and frustration when performing the task. Positive mental effort should be accompanied by high perceived performance and low frustration. To make the notion of positive mental effort operational, we return to the definition of this concept, specifying that it is part of the MWL construct.
JMIR Form Res 2025;9:e63491
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Previous studies have demonstrated that podcasts have positive effects on knowledge retention and test performance [5,6]. Multiple studies have previously been published on the effectiveness of remote learning during the COVID-19 pandemic via remote learning and web-based modules [7,8]. Most recently, 1 study aimed to measure podcast and blog utilization during the early months of the COVID-19 pandemic [9].
JMIR Med Educ 2025;11:e58100
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Model performance is based on training datasets. The incorporation of AI into traditional health care and medical education has had a substantial impact on medical practices [3]. It has accelerated diagnostic processes in radiography [4], pathology, endoscopy, and ultrasonography, has improved clinical decision-making, and has decreased the workloads of health care personnel. AI has had an impact on pharmaceutical development and management and medical education, resulting in a new paradigm [5].
JMIR Med Educ 2025;11:e58898
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However, current research shows that chatbot performance is uneven; in some areas or tasks, chatbot performance can reach more than 90% of the accuracy rate or satisfaction, and chatbot performance can even exceed that of some doctors; however, in some tasks, the answer provided is not valid or even wrong [13,14]. There are performance differences among different models, which are also affected by many factors, such as language, question type, and topic [15].
JMIR Med Inform 2025;13:e63924
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This study was conducted in 2023, comparing AI model performance against medical student performance data from March 21, 2023 (German questions) and June 16, 2023 (English questions). Error bars represent 95% CIs of the mean. Sample sizes (n) are provided for each group. AI: artificial intelligence.
JMIR Form Res 2024;8:e57592
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Electronic Health Record Data Quality and Performance Assessments: Scoping Review
Titles and abstracts were screened to include original research articles assessing the DQ and performance of all or part of a hospital’s EHR system. We looked for studies reporting on 1 or more aspects of DQ (the assessment of EHR data without consideration of follow-up actions) and data performance (the assessment of EHR data applications) as defined (Table 1).
Data quality and performance indicator definitions, mitigation strategies, and references.
a EHR: electronic health record.
JMIR Med Inform 2024;12:e58130
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In addition, the feasibility and promising performance of machine learning approaches in assessing T staging in lung cancer has been demonstrated [14]. However, few studies have reported the combination of deep learning and radiomics in predicting T staging in GC.
J Med Internet Res 2024;26:e56851
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