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Skip search results from other journals and go to results- 13 Journal of Medical Internet Research
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While AI tools such as PICO (Population, Intervention, Comparison, and Outcome) Portal, Distiller SR, Covidence (Veritas Health Innovation), and Rayyan (Rayyan Systems Inc) have already improved secondary evidence synthesis by streamlining data management and analysis [16], technologies like large language models (LLMs), including Chat GPT, are beginning to demonstrate potential for conducting systematic reviews autonomously, though human supervision remains essential to mitigate risks such as errors and hallucinations
JMIR Res Protoc 2025;14:e67248
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Most significant features contributing to the regression models evaluating the efficacy of each antihypertensive medication in the RIGIPREV study.
J Med Internet Res 2024;26:e54357
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Impact of a Digital Scribe System on Clinical Documentation Time and Quality: Usability Study
The introduction of large language models has disrupted this field, with many papers describing their potential value in clinical note generation and multiple companies now offering digital scribe systems [13-15]. However, an evaluation on the potential impact of such a system on documentation time, including the assessment of quality and user experiences is not available to date.
JMIR AI 2024;3:e60020
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The use of fixed model versions, as offered by some providers, is not practicable in the long term, as older models are often removed after the release of updates; in the case of Open AI, after 3 months [5].
An alternative is the use of nonproprietary AI models. In these models, the architecture as well as the trained parameters are available to the user.
JMIR Med Inform 2024;12:e59617
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Different models, such as basic, statistical, machine learning (support vector regression [SVR], random forest, gradient boosting, etc), and deep learning (long short-term memory and gated recurrent unit) models, were compared to identify the best opportunity for obtaining high-precision predictions.
There are different learning models for regression and classification. Given the nature of the data sets and the continuous nature of the variables to be predicted, a regression learning model was used.
JMIR Form Res 2024;8:e54009
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Considering the Role of Human Empathy in AI-Driven Therapy
Recent breakthroughs in artificial intelligence (AI) language models have elevated this vision, as evidenced by a growing body of literature indicating varying degrees of efficacy. For instance, studies demonstrate that digital chatbots are proficient in delivering psychoeducation and improving treatment adherence over short durations [3].
JMIR Ment Health 2024;11:e56529
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Finally, we propose a prompt engineering framework to build and deploy zero-shot NLP models for the clinical domain. This study covers 3 state-of-the-art LMs, including GPT-3.5, Gemini, and LLa MA-2, to assess the generalizability of the findings across various models. This work yields novel insights and guidelines for prompt engineering specifically for clinical NLP tasks.
JMIR Med Inform 2024;12:e55318
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In addition to known risk factors, it is unclear if existing prediction models for future cognitive impairment are equally accurate across different socioeconomic groups in China. Several published models have reported areas under the receiver operating characteristic curve (AUCs) greater than 0.80 in their development cohorts [5,7,8], but each model has only been tested on the general population. Nearly all existing models make predictions by leveraging measures of cognition, age, and education.
JMIR Aging 2024;7:e53240
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Traditionally, clinical practice has played a crucial role in nursing education, organized by guidance models. These models consist of procedures, meetings, and collaboration, aiming to facilitate the development of nursing students’ competencies in clinical practice through cooperation between health care and educational institutions [21].
JMIR Nursing 2024;7:e54443
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