Ryu Jeong Yeop, Chung Ho Yun, Choi Kang Young
Department of Plastic and Reconstructive Surgery, School of Medicine, Kyungpook National University, Daegu, Korea.
Cell & Matrix Research Institute, School of Medicine, Kyungpook National University, Daegu, Korea.
Arch Craniofac Surg. 2021 Oct;22(5):223-231. doi: 10.7181/acfs.2021.00507. Epub 2021 Oct 20.
The field of artificial intelligence (AI) is rapidly advancing, and AI models are increasingly applied in the medical field, especially in medical imaging, pathology, natural language processing, and biosignal analysis. On the basis of these advances, telemedicine, which allows people to receive medical services outside of hospitals or clinics, is also developing in many countries. The mechanisms of deep learning used in medical AI include convolutional neural networks, residual neural networks, and generative adversarial networks. Herein, we investigate the possibility of using these AI methods in the field of craniofacial surgery, with potential applications including craniofacial trauma, congenital anomalies, and cosmetic surgery.
人工智能(AI)领域正在迅速发展,AI模型在医学领域的应用越来越广泛,尤其是在医学成像、病理学、自然语言处理和生物信号分析方面。基于这些进展,使人们能够在医院或诊所之外接受医疗服务的远程医疗在许多国家也在不断发展。医学AI中使用的深度学习机制包括卷积神经网络、残差神经网络和生成对抗网络。在此,我们研究了在颅面外科领域使用这些AI方法的可能性,其潜在应用包括颅面创伤、先天性畸形和整容手术。