Darbari Anshuman, Kumar Krishan, Darbari Shubhankar, Patil Prashant L
CTVS Department, AIIMS, Rishikesh, 249203 India.
CSE Department, National Institute of Technology, Srinagar, Uttarakhand 246174 India.
Cardiothorac Surg. 2021;29(1):13. doi: 10.1186/s43057-021-00053-4. Epub 2021 Jul 3.
We have recently witnessed incredible interest in computer-based, internet web-dependent mechanisms and artificial intelligence (AI)-dependent technique emergence in our day-to-day lives. In the recent era of COVID-19 pandemic, this nonhuman, machine-based technology has gained a lot of momentum.
The supercomputers and robotics with AI technology have shown the potential to equal or even surpass human experts' accuracy in some tasks in the future. Artificial intelligence (AI) is prompting massive data interweaving with elements from many digital sources such as medical imaging sorting, electronic health records, and transforming healthcare delivery. But in thoracic surgical and our counterpart pulmonary medical field, AI's main applications are still for interpretation of thoracic imaging, lung histopathological slide evaluation, physiological data interpretation, and biosignal testing only. The query arises whether AI-enabled technology-based or autonomous robots could ever do or provide better thoracic surgical procedures than current surgeons but it seems like an impossibility now.
This review article aims to provide information pertinent to the use of AI to thoracic surgical specialists. In this review article, we described AI and related terminologies, current utilisation, challenges, potential, and current need for awareness of this technology.
最近,我们目睹了基于计算机、依赖互联网的机制以及依赖人工智能(AI)的技术在我们日常生活中的惊人发展。在最近的新冠疫情时代,这种非人类、基于机器的技术获得了巨大的发展动力。
具有人工智能技术的超级计算机和机器人在未来的某些任务中已显示出与人类专家的准确性相当甚至超越的潜力。人工智能(AI)正在促使海量数据与来自许多数字源的元素相互交织,如医学影像分类、电子健康记录,并正在改变医疗服务的提供方式。但在胸外科以及与之对应的肺部医学领域,AI的主要应用仍仅用于胸部影像解读、肺组织病理切片评估、生理数据解读和生物信号测试。由此产生的问题是,基于AI的技术或自主机器人是否能比当前的外科医生做得更好或提供更好的胸外科手术,但目前看来这似乎是不可能的。
这篇综述文章旨在为胸外科专家提供与AI应用相关的信息。在这篇综述文章中,我们描述了AI及相关术语、当前的应用、挑战、潜力以及当前对该技术的认知需求。