Reza Taufiqa, Bokhari Syed Faqeer Hussain
Medicine, Avalon University School of Medicine, Youngstown, USA.
Surgery, King Edward Medical University, Lahore, PAK.
Cureus. 2024 Mar 13;16(3):e56076. doi: 10.7759/cureus.56076. eCollection 2024 Mar.
Artificial intelligence (AI) and machine learning (ML) have emerged as transformative technologies in optimizing laparoscopic surgery, offering innovative solutions to enhance surgical precision, efficiency, and safety. This editorial explores the potential role of AI/ML across the surgical continuum, including preoperative optimization, intraoperative assistance, and postoperative care. It outlines the benefits of laparoscopic surgery compared to traditional open procedures and identifies current challenges such as technical difficulty and human error. The editorial discusses how AI and ML technologies can address these challenges, including patient selection and risk stratification, surgical planning and simulation, and personalized medicine approaches. Moreover, it examines the role of AI/ML in intraoperative assistance, such as instrument tracking and guidance, real-time tissue analysis, and the detection of potential complications. Postoperative care and follow-up are also explored, highlighting the potential of AI/ML in monitoring patient recovery, predicting and preventing complications, and tailoring rehabilitation plans. Ethical concerns surrounding data privacy and security, the lack of transparency in decision-making, potential job displacement, and regulatory frameworks are discussed as challenges to the widespread adoption of AI/ML in laparoscopic surgery. Finally, potential areas for further research and exploration are outlined, emphasizing interdisciplinary collaboration and the need for transparent and accountable AI systems. Overall, this editorial provides insights into the challenges and opportunities in harnessing AI/ML technologies to optimize laparoscopic surgery and improve patient outcomes.
人工智能(AI)和机器学习(ML)已成为优化腹腔镜手术的变革性技术,提供创新解决方案以提高手术精度、效率和安全性。这篇社论探讨了AI/ML在整个手术过程中的潜在作用,包括术前优化、术中辅助和术后护理。它概述了腹腔镜手术与传统开放手术相比的优势,并指出了当前面临的挑战,如技术难度和人为失误。社论讨论了AI和ML技术如何应对这些挑战,包括患者选择和风险分层、手术规划和模拟以及个性化医疗方法。此外,它还研究了AI/ML在术中辅助方面的作用,如器械跟踪与引导、实时组织分析以及潜在并发症的检测。还探讨了术后护理和随访,强调了AI/ML在监测患者恢复、预测和预防并发症以及定制康复计划方面的潜力。围绕数据隐私和安全、决策缺乏透明度、潜在的工作岗位替代以及监管框架等伦理问题被讨论为AI/ML在腹腔镜手术中广泛应用的挑战。最后,概述了进一步研究和探索的潜在领域,强调跨学科合作以及对透明且可问责的AI系统的需求。总体而言,这篇社论深入探讨了利用AI/ML技术优化腹腔镜手术并改善患者预后所面临的挑战和机遇。
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