<｜begin▁of▁sentence｜>### Instruction:
Imagine you're consulting on a case where the patient's recovery process can be visualized as a pathway, with nodes representing key milestones in their healing journey. The patient's progression follows a predictable sequence, analogous to a path graph with the milestones labeled as nodes [0, 1, 2, 3].

In order to strategize the optimal follow-up plan and ensure no steps are missed during post-operative assessments, could you illustrate the application of a method akin to the breadth-first search technique – specifically the bfs_edges function within the NetworkX framework? This would entail initiating the evaluation from the commencement of therapy, which corresponds to the source node 0, and sequentially listing the intermediary stages (edges) that are typically traversed during the patient's recuperation pathway.
### Response:
import networkx as nx

# Create a graph
G = nx.path_graph(4)

# Perform BFS and return edges
edges = list(nx.bfs_edges(G, source=0))
print(edges)
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