This invention relates to the field of
artificial intelligence in
oncology medicine, specifically disclosing a
system for quantifying residual
tumor burden in gastric
cancer, comprising: a
data acquisition and interaction terminal, an AI core
computing center, and a clinical precision decision support platform; the
data acquisition and interaction terminal is configured to acquire in parallel high-resolution digital
pathological slides of patients after
surgery, continuous physiological time-series characteristic sequences after
surgery, and the molecular expression abundance of POU4F1
transcription factor and TGF-β signaling pathway in
tumor tissue; the AI core
computing center includes a three-dimensional quantification unit for
pathological images, a dynamic correction unit for physiological
homeostasis, and a molecular phenotypic
decision unit; the three-dimensional quantification unit for
pathological images is used to automatically segment and obtain the geometric
mean diameter of the
primary tumor bed, the proportion of residual tumor in the
primary lesion, the number of positive
lymph nodes, and the proportion of residual tumor in the worst-regressed
lymph nodes; the technical solution of this invention can solve the problems of coarse quantification and large subjective bias.