人工智能
风险评估
责任
稳健性(进化)
计算机科学
计算机安全
业务
财务
生物化学
基因
化学
作者
Fréderic Van der Cruyssen,Pieter-Jan Verhelst,Reinhilde Jacobs
出处
期刊:Dental update
[Mark Allen Group]
日期:2024-01-02
卷期号:51 (1): 28-33
被引量:5
标识
DOI:10.12968/denu.2024.51.1.28
摘要
Third molar removal complication rates can be as high as 30%. Risk assessment tools may lower these rates. Artificial intelligence (AI) driven prediction models are a promising approach to predict possible unfavourable outcomes and cone beam computed tomography imaging may play an important role. AI prediction models are showing excellent results in research settings. To be implemented in clinical practice they will need to overcome some robustness, security, liability, and practical issues. If they do, AI prediction models can be integrated in electronic patient record systems by alerting clinicians in case of an imminent unfavourable outcome so it can be avoided. CPD/Clinical Relevance: Artificial intelligence-driven risk assessment tools will lower complications in third molar surgery.
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