<｜begin▁of▁sentence｜>### Instruction:
As a medical research scientist working at a pharmaceutical company, you are exploring ways to improve healthcare and develop new medical technologies. 
You have been given access to a network structure file, "as-22july06.gml", representing the connections within the healthcare community. 
You are wondering if the 'sbm_dl' function from the Community Discovery Library (cdlib) can be utilized to analyze the network and detect node communities using an efficient Monte Carlo and greedy heuristic for the inference of stochastic block models. 
Ultimately, you are seeking the output in JSON format, which represents the detected node communities within this healthcare network.
### Response:
import networkx as nx
from cdlib import algorithms

# Read the internet graph structure from a GML file
G = nx.read_gml('as-22july06.gml')

# Perform community detection using the Stochastic Block Model (SBM) with a greedy heuristic based on description length
communities = algorithms.sbm_dl(G)

# Output the result as JSON
result_json = communities.to_json()
print(result_json)
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