Deep Learning in Head and Neck Tumor Multiomics Diagnosis and Analysis: Review of the Literature - Wang, Xi; Li, Bin-bin (Frontiers in Genetics, 2021)
Head-and-neck tumours are the sixth most common neoplasms. Multi-omics integrates multiple dimensions of clinical, pathologic, radiological, biological data and has potential for tumour diagnosis and analysis. Deep learning (DL), a type of artificial intelligence (AI), is applied in medical image analysis. Among DL techniques, convolution neural network (CNN) is used for image segmentation, detection and classification, and in computer-aided diagnosis. Here we reviewed multi-omics image analysis of head-and-neck tumours using CNN and other DL neural networks. We also evaluated its application in early tumour detection, classification, prognosis/metastasis prediction and the signing-out of the reports. Finally, we highlighted the challenges and potential of these techniques.