充分利用临床奖学金——机器人、数据科学和人工智能

Luis Ribeiro, Nicholas Raison
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引用次数: 0

摘要

包括机器人技术、数据科学和人工智能(AI)在内的外科技术的快速发展,使现代外科医生所需的技能与传统培训计划之间的差距越来越大。从历史上看,这一差距导致了专业临床奖学金的发展,这对于寻求掌握这些新兴技术的外科医生来说已经成为必不可少的。机器人手术和人工智能需要新的能力,但这些并没有完全融入当前的外科课程。机器人手术和数字健康的奖学金提供结构化的实践培训,将理论知识与实际应用相结合。人工智能与机器人技术的结合在提高术中表现和外科教育方面显示出巨大的希望。数字奖学金,如Topol数字奖学金和NHS临床人工智能奖学金,专注于发展医疗保健领域数字化转型的领导力,为外科医生提供数据分析、机器学习和人工智能应用方面的技能。随着外科手术与数据科学和人工智能越来越紧密地联系在一起,这些奖学金不仅解决了目前的教育差距,而且为技术熟练的外科劳动力铺平了道路,能够利用先进的技术来加强患者护理。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Making the most of clinical fellowships – robotics, data science and artificial intelligence
The rapid advancement of surgical technologies, including robotics, data science and artificial intelligence (AI), has created a widening gap between the skills required by modern surgeons and the offerings of traditional training programmes. Historically, this gap led to the development of specialized clinical fellowships, which have now become essential for surgeons seeking to master these emerging technologies. Robotic surgery and AI demand new competencies, yet these are not fully integrated into current surgical curricula. Fellowships in robotic surgery and digital health offer structured, hands-on training, combining theoretical knowledge with practical application. Integration of AI with robotics has shown significant promise in improving intraoperative performance and surgical education. Digital fellowships, such as the Topol Digital Fellowship and NHS Clinical AI Fellowship, focus on developing leadership in digital transformation within healthcare, equipping surgeons with skills in data analysis, machine learning, and AI applications. As surgery becomes increasingly intertwined with data science and AI, these fellowships are not only addressing current educational gaps but also paving the way for a technologically adept surgical workforce, capable of leveraging advanced technologies to enhance patient care.
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