Advances in innovative applications of artificial intelligence combined with intraoperative neuromonitoring technology in thyroid surgery
10.3760/cma.j.cn115807-20250630-00200
- VernacularTitle:人工智能结合甲状腺术中神经监测技术的创新应用进展
- Author:
Heyang JIAO
1
;
Yingying WANG
1
;
Jiedong KOU
1
;
Peiyao WANG
1
;
Yishen ZHAO
1
;
Hui SUN
1
Author Information
1. 吉林大学中日联谊医院甲状腺外科 吉林省外科转化医学重点实验室 吉林省甲状腺疾病防治工程实验室，长春 130000
- Publication Type:Journal Article
- Keywords:
Intraoperative neural monitoring;
Thyroid surgery;
Deep learning;
Voice function;
Multimodal fusion
- From:
Chinese Journal of Endocrine Surgery
2025;19(5):783-786
- CountryChina
- Language:Chinese
-
Abstract:
Intraoperative neural monitoring (IONM) is a critical technique for the protection of recurrent laryngeal nerve (RLN) function during thyroid surgery. In recent years, continuous innovations in IONM have established it as a cornerstone of modern thyroid surgery. However, current methodologies still exhibit limitations in the accurate assessment of neural function, and guidelines have yet to provide clear strategies for managing patients with intraoperative signal loss who subsequently develop postoperative voice disorders. This article reviews representative advances in the application of deep learning to bioelectrophysiological signals and systematically summarizes the use of deep learning in the field of voice medicine, thereby exploring the feasibility of integrating IONM with deep learning technologies.
