Artificial intelligence technique in detection of early esophageal cancer
Lu-Ming Huang, Wenjuan Yang, Zhiyin Huang, Chengwei Tang, Jing Li
Abstract
image analysis for classification to real-time detection of early esophageal neoplasia. When AI technique comes to the pathological diagnosis, borderline lesions that are difficult to determine may become easier than before. In gene diagnosis, due to the lack of tissue specificity of gene diagnostic markers, they can only be used as supplementary measures at present. In predicting the risk of cancer, there is still a lack of prospective clinical research to confirm the accuracy of the risk stratification model.
Topics & Concepts
Esophageal cancerMedicineCancerArtificial intelligenceInternal medicineComputer scienceEsophageal Cancer Research and TreatmentLung Cancer Diagnosis and TreatmentGastric Cancer Management and Outcomes