<｜begin▁of▁sentence｜>### Instruction:
As a plastic surgeon, think of a scenario where you're presented with two groups of clinical cases for intricate reconstructive procedures. The first group comprises 10 potential surgeries involving 20 specific surgical interventions, while the second group consists of 20 cases with 40 interventions. In an effort to optimize the operating schedule and resource allocation, you consider the interconnectedness of operations within each group and the likelihood of needing to coordinate between the groups.

You aim for a collaborative approach where approximately 80% of the focus is on the synergies within each group of surgeries and 20% of your efforts directed at harmonizing between the two groups. Imagine using advanced biomedical informatics tools to simulate this situation. Could you frame this as a network construction task using specialized software to visualize and analyze the relationships within and between surgical case groups? Would you then be able to identify the total number of surgeries and interventions you'd be managing within this network model?
### Response:
import networkx as nx

constructor = [(10, 20, 0.8), (20, 40, 0.8)]
G = nx.random_shell_graph(constructor)

print('Number of nodes:', G.number_of_nodes())
print('Number of edges:', G.number_of_edges())
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