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References from Rethinking Pediatric Asthma Education Through Large Language Model Generation and Simplification: Randomized Double-Blind Study. Local targets link to admitted publications; unresolved targets remain external evidence.
Using ChatGPT for writing articles for patients’ education for dermatological diseases: a pilot study
10.4103/idoj.idoj_72_23 · External reference
Health literacy and online educational resources: an opportunity to educate patients
10.2214/ajr.14.13086 · External reference
Exploring the role of artificial intelligence in smart healthcare: a capability and function-oriented review
10.3390/healthcare13141642 · External reference
Large language models in medicine
10.1038/s41591-023-02448-8 · External reference
ChatGPT: the transformative influence of generative AI on science and healthcare
10.1016/j.jhep.2023.07.028 · External reference
"Doctor ChatGPT, can you help me?" The patient's perspective: cross-sectional study
10.2196/58831 · External reference
Assessing the utility of ChatGPT in simplifying text complexity of patient educational materials
10.7759/cureus.55304 · External reference
Economic evaluations of digital health interventions for children and adolescents: systematic review
10.2196/45958 · External reference
Artificial intelligence for mental health: a narrative review of applications, challenges, and future directions in digital health
10.1177/20552076251395548 · External reference
Assessing the efficacy of large language models in health literacy: a comprehensive cross-sectional study
10.59249/ztoz1966 · External reference
ChatGPT and other large language models for parents’ questions about childhood asthma: a comparative study
10.1183/13993003.00254-2025 · External reference
Diagnostic accuracy of a large language model in pediatric case studies
10.1001/jamapediatrics.2023.5750 · External reference
A context-based chatbot surpasses trained radiologists and generic ChatGPT in following the ACR appropriateness guidelines
10.1148/radiol.230970 · External reference
How AI responds to common lung cancer questions: ChatGPT vs Google Bard
10.1148/radiol.230922 · External reference
Unresolved reference
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One hundred questions and answers on the Chinese Children’s Asthma Action Plan [Article in Chinese]
10.3760/cma.j.cn101070-20210310-00289 · External reference
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Prompt engineering as an important emerging skill for medical professionals: tutorial
10.2196/50638 · External reference
Association between eHealth literacy in online health communities and patient adherence: cross-sectional questionnaire study
10.2196/14908 · External reference
Relationship between internet health information and patient compliance based on trust: empirical study
10.2196/jmir.9364 · External reference
eWOM source credibility, perceived risk and food product customer’s information adoption
10.1016/j.chb.2016.09.034 · External reference
Operationalisierung von vertrauen in journalismus [Article in German]
10.5771/1615-634x-2003-1-5 · External reference
How experts’ use of medical technical jargon in different types of online health forums affects perceived information credibility: randomized experiment with laypersons
10.2196/jmir.8346 · External reference
Patient–physician interaction and trust in online health community: the role of perceived usefulness of health information and services
10.3390/ijerph17010139 · External reference
Engagement in healthcare systems: adopting digital tools for a sustainable approach
10.3390/su11010220 · External reference
Factors affecting public adoption of COVID-19 prevention and treatment information during an infodemic: cross-sectional survey study
10.2196/23097 · External reference
CRIE: an automated analyzer for Chinese texts
10.3758/s13428-015-0649-1 · External reference
Evaluation of quality and readability of over-the-counter medication package inserts
10.1016/j.sapharm.2022.03.012 · External reference
Evaluation of the quality and readability of online information about breast cancer in China
10.1016/j.pec.2020.09.012 · External reference
Evaluation of the quality and readability of ChatGPT responses to frequently asked questions about myopia in traditional Chinese language
10.1177/20552076241277021 · External reference
Artificial intelligence-generated answers to patients' questions on asthma: the artificial intelligence responses on asthma study
10.1016/j.jaip.2025.04.051 · External reference
Doctor versus artificial intelligence: patient and physician evaluation of large language model responses to rheumatology patient questions in a cross-sectional study
10.1002/art.42737 · External reference
Large language models in patient education: a scoping review of applications in medicine
10.3389/fmed.2024.1477898 · External reference
Five strategies for optimizing instructional materials: instructor- and learner-managed cognitive load
10.1007/s10648-021-09606-9 · External reference
The synergy of embodied cognition and cognitive load theory for optimized learning
10.1038/s41562-025-02152-2 · External reference
Mitigating cognitive biases in clinical decision-making through multi-agent conversations using large language models: simulation study
10.2196/59439 · External reference
Evaluation of ChatGPT as a diagnostic tool for medical learners and clinicians
10.1371/journal.pone.0307383 · External reference
Perspectives and experiences with large language models in health care: survey study
10.2196/67383 · External reference
A framework for human evaluation of large language models in healthcare derived from literature review
10.1038/s41746-024-01258-7 · External reference
New frontiers in health literacy: using ChatGPT to simplify health information for people in the community
10.1007/s11606-023-08469-w · External reference
Quality criteria were proposed for measurement properties of health status questionnaires
10.1016/j.jclinepi.2006.03.012 · External reference
The simplicity complex: exploring simplified health messages in a complex world
10.1093/heapro/daq075 · External reference
A user-study measuring the effects of lexical simplification and coherence enhancement on perceived and actual text difficulty
10.1016/j.ijmedinf.2013.03.001 · External reference
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Explainable AI in clinical decision support systems: a meta-analysis of methods, applications, and usability challenges
10.3390/healthcare13172154 · External reference
Does AI explainability affect physicians’ intention to use AI?
10.1016/j.ijmedinf.2022.104884 · External reference
Current applications and challenges in large language models for patient care: a systematic review
10.1038/s43856-024-00717-2 · External reference
Generative artificial intelligence and ethical considerations in health care: a scoping review and ethics checklist
10.1016/s2589-7500(24)00143-2 · External reference
Ethical and regulatory challenges of large language models in medicine
10.1016/s2589-7500(24)00061-x · External reference