Abstract：
Artificial intelligence (AI), particularly deep learning, has revolutionized various fields through its ability to model complex, noisy systems with high accuracy. Driven by advancements in deep neural networks (DNNs), hardware, and data digitization, deep learning now rivals human performance in many tasks. This review focuses on the application of deep learning in otolaryngology, specifically within laryngology and otology. By leveraging digital archives of acoustic and other clinical data, these specialties are beginning to integrate DNNs to enhance patient care. We examine key studies, challenges, and the potential of AI to transform these subdisciplines.
摘要：
人工智能(AI)特别是深度学习，通过其建模复杂的能力彻底改变了各个领域，高精度的嘈杂系统。在深度神经网络(DNN)的进步的推动下，硬件,和数据数字化，深度学习现在可以在许多任务中与人类的表现相媲美。本文就深度学习在耳鼻喉科的应用进行综述,特别是在喉科和耳科。通过利用声学和其他临床数据的数字档案，这些专业开始整合DNN，以加强患者护理。我们研究关键研究，挑战,以及人工智能改变这些分支学科的潜力。
