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Revolutionizing gastrointestinal endoscopy: the emerging role of large language models

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EDITORIAL

참고문헌 (10)

  1. Bang CS, "Artificial intelligence in the analysis of upper gastro intestinal disorders", Korean J Helicobacter Up Gastrointest Res, 21, pp.300~310 (2021)
  2. Gong EJ, "Clinical decision support system for all stages of gastric carcinogenesis in real-time endoscopy : model es tablishment and validation study", J Med Internet Res, 25, pp.e50448~ (2023)
  3. Gong EJ, "Deep learning-based clinical decision support system for gastric neoplasms in real-time endoscopy : devel opment and validation study", Endoscopy, 55, pp.701~708 (2023)
  4. Kim HJ, "Application of machine learning based on structured medical data in gastroenterology", Biomimetics(Basel), 8, pp.512~ (2023)
  5. Buzzaccarini G, "The promise and pitfalls of AI-generated anatomical images : evaluating midjourney for aesthetic surgery applications", Aesthetic Plast Surg, 48, pp.18741883~ (2024)
  6. Chin H, "The potential of chatbots for emo tional support and promoting mental well-being in different cul tures : mixed methods study", J Med Internet Res, 25, pp.e51712~ (2023)
  7. Ge J, "Development of a liver disease-specific large language model chat Interface using retrieval augmented gen eration", Hepatology, 80, pp.1158~1168 (2024)
  8. Savage T, "A large language model screening tool to target patients for best practice alerts : development and validation", JMIR Med Inform, 11, pp.e49886~ (2023)
  9. Zack T, "Assessing the potential of GPT-4to perpetuate racial and gender biases in health care : a model evalua tion study", Lancet Digit Health, 6, pp.e12~e22 (2024)
  10. Hastings J, "Preventing harm from non-conscious bias in medical generative AI", Lancet Digit Health, 6, pp.e2~e3 (2024)

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