Artificial Intelligence Model for a Distinction between Early-Stage Gastric Cancer Invasive Depth T1a and T1b
Tsung‐Hsing Chen, Chang‐Fu Kuo, Chieh Lee, Ta‐Sen Yeh, Jui Lan, Shih‐Chiang Huang
Abstract
Our findings suggest that the AI model can effectively replace EUS and CT in early GC staging, with an average validation accuracy rate of 86.18% for the original dataset from Linkou Cheng Gun Memorial Hospital and 82.14% for the external validation dataset from Kaohsiung Cheng Gun Memorial Hospital. Moreover, our AI model's accuracy rate outperformed the average EUS and CT rates in previous literature (around 70%).
Topics & Concepts
Stage (stratigraphy)CancerComputer scienceArtificial intelligenceMedicineInternal medicineBiologyPaleontologyGastric Cancer Management and Outcomes