With the development of socioeconomic and computer science and technology, people have paid more and more attention to physical health and living convenience, network precision medicine enters people's lives. Because that teamwork is needed in the medical process, how to recommend a doctor to form a team becomes important. Instead of using recommendation algorithm, the paper recommends doctors based on community detection. Firstly, 37144 pairs of doctors with labels based on thesis cooperation relationship were obtained through web crawler, secondly, find the connected subgraph with the union check set, thirdly, create the graph with the doctors as nodes, the cooperation relationship between doctors as the edges, and cut the graph with the algorithm of spectral clustering until the connected graphs have approximately five layers of relations. Then take the number of cooperative papers as the weight of edges. Recommend a doctor with the doctors who are in at least the third layer and with a higher weight score in the same community. At the same time, the paper suggests the doctors of the same community make the team. From the perspective of community detection, this paper solves the problems of doctor recommendation and team building, which results in more ideal results. And the community visualization paves the way for the recommendation system to be completed in the future.

Li Guo, Chenning Du. Doctor recommendation via community detection. Academic Journal of Computing & Information Science (2021), Vol. 4, Issue 3: 68-76. https://doi.org/10.25236/AJCIS.2021.040311.

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