Classification and detection of dental images using meta-learning  

作　　者：Pradeep Kumar Yadalam Raghavendra Vamsi Anegundi Mario Alberto Alarcón-Sánchez Artak Heboyan 

机构地区：[1]Department of Periodontics,Saveetha Dental College and Hospital,Saveetha Institute of Medical and Technical Sciences,Saveetha University,Chennai 600077,Tamil Nadu,India [2]South Pacific Dental Institute,Chilpancingo de los Bravo 39022,Guerrero,Mexico [3]Department of Prosthodontics,Faculty of Stomatology,Yerevan State Medical University after Mkhitar Heratsi,Yerevan 0025,Armenia

出　　处：《World Journal of Clinical Cases》2024年第32期6559-6562,共4页世界临床病例杂志（英文）

摘　　要：Meta-learning of dental X-rays is a machine learning technique that can be used to train models to perform new tasks quickly and with minimal input.Instead of just memorizing a task,this is accomplished through teaching a model how to learn.Algorithms for meta-learning are typically trained on a collection of training problems,each of which has a limited number of labelled instances.Multiple Xray classification tasks,including the detection of pneumonia,coronavirus disease 2019,and other disorders,have demonstrated the effectiveness of meta-learning.Meta-learning has the benefit of allowing models to be trained on dental X-ray datasets that are too few for more conventional machine learning methods.Due to the high cost and lengthy collection process associated with dental imaging datasets,this is significant for dental X-ray classification jobs.The ability to train models that are more resistant to fresh input is another benefit of meta-learning.

关 键 词：Artificial intelligence META-LEARNING Dental diagnosis Image segmentation Medical image interpretation Dental radiography 

分 类 号：R78[医药卫生—口腔医学]