Large Language Models in Gastroenterology and Gastrointestinal Surgery: A New Frontier in Patient Communication and Education.

IF 1.4 Q4 GASTROENTEROLOGY & HEPATOLOGY
Gastroenterology Research Pub Date : 2025-04-01 Epub Date: 2025-03-24 DOI:10.14740/gr2011
Dushyant Singh Dahiya, Hassam Ali, Vishali Moond, M Danial Ali Shah, Christina Santana, Noor Ali, Abu Baker Sheikh, Muhammad Ahmad Nadeem, Aqsa Munir, Mohammed A Quazi, Hareesha Rishab Bharadwaj, Amir Humza Sohail
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引用次数: 0

Abstract

When integrated into healthcare, large language models (LLMs) have transformative and revolutionary effects, including significant potential for improving patient care and streamlining clinical processes. However, one specialty that particularly requires data on LLM use is gastroenterology and gastrointestinal surgery, a gap we sought to address in our research. Advanced artificial intelligence (AI) systems like LLMs have demonstrated the ability to mimic human communication, assist in diagnosis, provide patient education, and support medical research simultaneously. Despite these advantages, challenges such as biases, data privacy concerns, and lack of transparency in decision-making remain critical. The role of regulations in mitigating these risks is widely debated, with proponents advocating for structured oversight to enhance trust and patient safety, while others caution against potential barriers to innovation. Rather than replacing human expertise, AI should be integrated thoughtfully to complement clinical decision-making. Ensuring a balanced approach requires collaboration between medical professionals, AI developers, and policymakers to optimize its responsible implementation in healthcare.

胃肠病学和胃肠外科的大型语言模型:患者沟通和教育的新前沿。
当集成到医疗保健中时,大型语言模型(llm)具有变革性和革命性的影响,包括改善患者护理和简化临床流程的巨大潜力。然而,一个特别需要LLM使用数据的专业是胃肠病学和胃肠外科,这是我们在研究中寻求解决的一个空白。法学硕士等先进的人工智能(AI)系统已经展示了模拟人类交流、协助诊断、提供患者教育和同时支持医学研究的能力。尽管有这些优势,但偏见、数据隐私问题和决策缺乏透明度等挑战仍然至关重要。监管在减轻这些风险方面的作用存在广泛争议,支持者主张进行结构化监管,以增强信任和患者安全,而其他人则警告要提防创新的潜在障碍。人工智能不应该取代人类的专业知识,而应该被深思熟虑地整合,以补充临床决策。确保平衡的方法需要医疗专业人员、人工智能开发人员和政策制定者之间的协作,以优化其在医疗保健领域的负责任实施。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Gastroenterology Research
Gastroenterology Research GASTROENTEROLOGY & HEPATOLOGY-
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