<｜begin▁of▁sentence｜>### Instruction:
As a telemedicine physician providing remote medical consultations, diagnoses, and treatments via telecommunication technologies, you've received a request from a healthcare research team. They've been using a specialized tool called NetworkX to analyze the interconnectedness of patient data in a network graph format, which they've saved as "graph_data.gml". 

The team needs assistance in utilizing the "eigen_centrality" function within NetworkX to compute the eigenvector centrality for each node in the patient network. Subsequently, they want to determine the number of nodes that have been assigned a computed eigenvector centrality value. This information will aid in their research on identifying key nodes within the patient network for targeted interventions and treatment strategies.
### Response:
from networkx.algorithms.centrality import eigen_centrality
import networkx as nx

# Create a NetworkX graph
G = nx.read_gml('graph_data.gml')

# Compute the eigenvector centrality
eigen_centralities = eigen_centrality(G)

# Get the number of nodes with calculated eigenvector centrality
num_nodes_with_eigen_centrality = len(eigen_centralities)

# Print the number
print(f'Number of nodes with eigenvector centrality: {num_nodes_with_eigen_centrality}')
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