Deep Learning in Head and Neck Tumor Multiomics Diagnosis and Analysis: Review of the Literature

Frontiers in Genetics

Bin-bin Li¹  Xi Wang² 

[1] Beijing Key Laboratory of Digital Stomatology, Beijing, China;;National Clinical Research Center for Oral Diseases &;National Engineering Laboratory for Digital and Material Technology of Stomatology &;Department of Oral Pathology, Peking University School and Hospital of Stomatology &

关键词: artificial intelligence;    deep learning;    head and neck tumors;    diagnosis;    multi-omics;   

DOI  :  10.3389/fgene.2021.624820

来源: DOAJ

【 摘 要 】

Head and neck tumors are the sixth most common neoplasms. Multiomics integrates multiple dimensions of clinical, pathologic, radiological, and biological data and has the potential for tumor diagnosis and analysis. Deep learning (DL), a type of artificial intelligence (AI), is applied in medical image analysis. Among the DL techniques, the convolution neural network (CNN) is used for image segmentation, detection, and classification and in computer-aided diagnosis. Here, we reviewed multiomics image analysis of head and neck tumors using CNN and other DL neural networks. We also evaluated its application in early tumor detection, classification, prognosis/metastasis prediction, and the signing out of the reports. Finally, we highlighted the challenges and potential of these techniques.

【 授权许可】

Unknown