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Skip search results from other journals and go to results- 19 Journal of Medical Internet Research
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Perspectives and Experiences With Large Language Models in Health Care: Survey Study
Reference 3: The potential for artificial intelligence in healthcare Reference 4: The role of artificial intelligence in healthcare: a structured literature review Reference 8: Efficient healthcare with large language models: optimizing clinical workflow and enhancing Reference 32: An exploratory survey about using ChatGPT in education, healthcare, and research Reference 38: A critical review of global digital divide and the role of technology in healthcarehealthcare healthcare worker
J Med Internet Res 2025;27:e67383
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Choosing the Best Digital Health Literacy Measure for Research: Mixed Methods Study
healthcare
J Med Internet Res 2025;27:e59807
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Reference 3: A guide to deep learning in healthcarehealthcare
J Med Internet Res 2025;27:e57257
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Initial CFA using the original SHAIP tool showed that question 10 “I believe that should AI technology make an error, full responsibility lies with the healthcare professional” had a low correlation (0.097, P=.26) with the preparedness for AI factor.
JMIR Form Res 2024;8:e57204
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We conducted a qualitative focus group study with patients with cancer and survivors in Canada as part of the Canadian Network for Learning Healthcare Systems and Cost Effective ‘Omics Innovation (CLEO) project, an initiative evaluating 6 precision oncology programs in Canada to inform the design of a learning health care system for cancer research and care [27].
J Med Internet Res 2024;26:e63155
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Large Language Models and Empathy: Systematic Review
Reference 5: ChatGPT utility in healthcare education, research, and practice: systematic review on thehealthcare
J Med Internet Res 2024;26:e52597
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Interoperable data were used as the TG made anonymized, standardized datasets available for extraction using Health Level 7-Fast Healthcare Interoperability Resources (HL7-FHIR), contributing to the national COVID-19 Data Exchange Platform (CODEX) [15] and enabling epidemiological evaluation based on the German Corona Consensus (GECCO) [16] dataset.
JMIR Form Res 2024;8:e57608
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Reference 3: Healthcare providers' and deaf patients' interpreting preferences for critical care and Reference 6: Deaf patients' preferred communication in clinical settings: implications for healthcarehealthcare
JMIR Res Protoc 2024;13:e64590
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