Information processing apparatus, information processing method, and non-transitory computer readable medium

An information processing method comprising:

• classifying cells in an image of a tumor microenvironment obtained from a patient into a plurality of cell groups;
• extracting positions, in the image, of the cells included in the plurality of cell groups;
• creating a graph by assigning nodes to the cells included in the plurality of cell groups based on the extracted positions, connecting the nodes with edges, assigning to each of the nodes a feature quantity indicating a feature of the corresponding cell, and assigning to each of the edges a feature quantity indicating a relationship between two cells corresponding to two nodes connected by the edge;
• and
• modeling, using a graph neural network (GNN), spatial relationships between cells in the graph based on the assigned feature quantities of the nodes and the edges.

A non-transitory computer readable medium storing an information processing program for causing a computer to execute information processing, the program causing the computer to execute:

• classification processing of classifying cells in an image of a tumor microenvironment obtained from a patient into a plurality of cell groups;
• spatial information extraction processing of extracting positions, in the image, of the cells included in the plurality of cell groups;
• graph creation processing of creating a graph by assigning nodes to the cells included in the plurality of cell groups based on the extracted positions, connecting the nodes with edges, assigning to each of the nodes a feature quantity indicating a feature of the corresponding cell, and assigning to each of the edges a feature quantity indicating a relationship between two cells corresponding to two nodes connected by the edge;
• and
• modeling processing of modeling, using a graph neural network (GNN), spatial relationships between cells in the graph based on the assigned feature quantities of the nodes and the edges.