Tele-surgery and remote procedures: The future of global surgical care
Devesh Nagpure, Sheetal Asutkar
- 发表年份
- 2024
- 引用次数
- 6
- 访问权限
- 开放获取
摘要
The growing global demand for surgical care contrasts sharply with the limited access to high-quality services in resource-limited regions, driving innovations like tele-surgery and remote surgical techniques. Tele-surgery employs robotic systems, high-resolution imaging, and advanced telecommunications to perform intricate procedures across vast distances. Since its inception with the landmark "Lindbergh Operation" in 2001, tele-surgery has benefited from significant technological advancements, including AI-powered platforms and robotic systems such as the da Vinci Surgical System. These technologies enable minimally invasive procedures, reduce recovery times, and enhance patient outcomes. Tele-surgery offers transformative potential in addressing healthcare inequities, particularly in underserved or conflict-affected regions, and during global emergencies like pandemics. It also provides substantial educational opportunities by enabling real-time observation of surgeries and fostering knowledge exchange through virtual and augmented reality tools. Despite its promise, tele-surgery faces challenges that hinder its widespread adoption. These include technological constraints like latency, inadequate infrastructure in low-income areas, cybersecurity risks, and the high costs of robotic systems. Ethical and legal considerations, including liability for errors and data privacy concerns, further complicate its implementation. Nevertheless, advancements in AI, machine learning, and 5G technology are expected to enhance tele-surgery’s efficiency and affordability, paving the way for its integration into global healthcare systems. With the potential to bridge healthcare access gaps and revolutionize surgical care delivery, tele-surgery represents a pivotal step toward equitable healthcare. However, overcoming current technological, financial, and legal barriers remains essential to realizing its full potential.
关键词
相关论文
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
A new optimizer using particle swarm theory
R.C. Eberhart, James Kennedy
2002