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Skip search results from other journals and go to results- 18 Journal of Medical Internet Research
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To address this, this study applies large language models (LLMs), which excel at interpreting nuanced, unstructured textual data. Unlike traditional machine learning models—which require extensive feature engineering and often miss deeper linguistic or conceptual structures—LLMs can process entire sentences or paragraphs as coherent units, capturing context, tone, and latent psychological meaning [12].
JMIR Nursing 2025;8:e73672
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One low-cost potential solution that could assist health care workers in lower income countries is online clinical assistants powered by artificial intelligence (AI) large language models (LLMs). These clinical assistants could help clinicians to triage patients and identify the causes of their conditions in settings where secondary or tertiary specialist care is unavailable.
The advent of chatbots and AI within the field of medicine is not a new occurrence.
JMIR Form Res 2025;9:e64986
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We appreciate the their thoughtful input, which strengthens our discussion on the role of large language models (LLMs) in health care.
Our article aimed to provide a forward-looking perspective on LLMs’ potential in medicine, prioritizing conceptual insights over granular technical details. The reviewers’ points regarding multimodal data integration, image analysis, and resource allocation align with emerging research and underscore LLMs’ transformative capabilities.
J Med Internet Res 2025;27:e73144
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The authors synthesized all the possible applications of large language models (LLMs) very well, not only detailing applications related to clinical medicine, but also offering some examples of LLMs’ potential in a broader hospital environment and in public health policies.
J Med Internet Res 2025;27:e71618
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It is positioned to benefit from advances in an even wider array of disciplines, including bioinformatics, data science, machine learning, artificial intelligence (AI), natural language processing, large language models (LLMs), systems pharmacology, pharmacogenomics, pharmacometabolomics, and health informatics [2-7].
JMIR AI 2025;4:e65481
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The recent rapid innovation of large language models (LLMs) has led to the emergence of Chat GPT, which is the first LLM to provide the data basis and performance to support or carry out medical research and clinical decisions. Nevertheless, the clinical application is currently viewed with a degree of skepticism, as Chat GPT, especially in the earlier versions 2 and 3, demonstrated a marked tendency to “confabulate,” to fabricate statements and even references [2].
JMIR Form Res 2025;9:e63857
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In recent years, large language models (LLMs) based on transformer architectures, such as Chat GPT (Open AI), Gemini (Google Deep Mind), and Claude (Anthropic), have emerged as promising tools in the medical domain [13].
J Med Internet Res 2025;27:e67830
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LLMs are generally pretrained on large corpora of texts from the internet. As a result, inherent biases in human language can influence model outputs. Recent LLMs, such as GPT-4o, undergo posttraining alignment to reduce biased responses. This serves as the first line of defense against bias. Second, in our case, the LLM is instructed to return a single label (yes or no), which may further reduce the potential for hallucinations and bias.
JMIR Med Inform 2025;13:e67706
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The recent introduction of large language models (LLMs) for public use has generated both excitement and debate. Their adoption has rapidly grown across various human activities [6]. Many foresee the immense potential benefits of applying such technology to medical practice, while others harbor concerns about the dangers it might pose if left unregulated and misaligned [7-12].
Without a doubt, LLMs like Chat GPT represent a new generation of CDSS with unparalleled assistance capabilities.
JMIR Med Educ 2025;11:e55709
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LLMs are models trained on large amounts of textual data that are capable of generating language similar to that of humans. LLMs’ capabilities span a diverse array of tasks, including question-answering, summarization, translation, and conversing. The development and integration of LLMs is advancing rapidly across different sectors. In particular, LLMs demonstrate impressive performance in automated analyses and syntheses of data [6].
J Med Internet Res 2025;27:e64364
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