论文标题
手术中的人工智能：神经网络和深度学习
Artificial Intelligence in Surgery: Neural Networks and Deep Learning
论文作者
论文摘要
深度神经网络的最新人工智能成功，从自动驾驶汽车到放射学和病理学的计算机辅助诊断。高标准的数据密集型手术过程可以从这种计算方法中受益匪浅。但是，外科医生和计算机科学家应合作开发和评估对患者和医疗保健系统价值的深度学习应用。本章和随附的动手材料是为愿意了解神经网络背后的直觉，熟悉深度学习概念和任务的外科医生而设计的，掌握了在手术中实施深度学习模型的含义，并最终欣赏了手术中深神经网络的具体挑战和局限性。有关相关的动手材料，请参阅https://github.com/camma-public/ai4surgery。
Deep neural networks power most recent successes of artificial intelligence, spanning from self-driving cars to computer aided diagnosis in radiology and pathology. The high-stake data intensive process of surgery could highly benefit from such computational methods. However, surgeons and computer scientists should partner to develop and assess deep learning applications of value to patients and healthcare systems. This chapter and the accompanying hands-on material were designed for surgeons willing to understand the intuitions behind neural networks, become familiar with deep learning concepts and tasks, grasp what implementing a deep learning model in surgery means, and finally appreciate the specific challenges and limitations of deep neural networks in surgery. For the associated hands-on material, please see https://github.com/CAMMA-public/ai4surgery.
