卷积神经网络
人工智能
深度学习
计算机科学
人工神经网络
机器学习
模式
模态(人机交互)
过程(计算)
口腔医学
医学物理学
医学
牙科
社会科学
操作系统
社会学
作者
Anna Luíza Damaceno Araújo,Viviane Mariano da Silva,Maíra Suzuka Kudo,Eduardo Santos Carlos de Souza,Cristina Saldivia-Siracusa,Daniela Giraldo-Roldán,Marcio Ajudarte Lopes,Pablo Agustin Vargas,Syed Ali Khurram,Alexander T Pearson,Luiz Paulo Kowalski,André Carlos Ponce de Leon Ferreira de Carvalho,Alan Roger Santos-Silva,Matheus Cardoso Moraes
摘要
Artificial intelligence models and networks can learn and process dense information in a short time, leading to an efficient, objective, and accurate clinical and histopathological analysis, which can be useful to improve treatment modalities and prognostic outcomes. This paper targets oral pathologists, oral medicinists, and head and neck surgeons to provide them with a theoretical and conceptual foundation of artificial intelligence-based diagnostic approaches, with a special focus on convolutional neural networks, the state-of-the-art in artificial intelligence and deep learning.The authors conducted a literature review, and the convolutional neural network's conceptual foundations and functionality were illustrated based on a unique interdisciplinary point of view.The development of artificial intelligence-based models and computer vision methods for pattern recognition in clinical and histopathological image analysis of head and neck cancer has the potential to aid diagnosis and prognostic prediction.
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