[Objective] This paper investigates the decision-making mechanism of patients choosing doctors, aiming to build a better physician recommendation system.[Methods] First, we used Word2Vec to train the word vector model, and calculated the similarity between patients and doctors. Then, we analyzed the decision-making behaviors of patients choosing doctors. Finally, we combined the scores of doctors based on their similarity with patient needs and the latter’s decision mechanism to generate a recommended list.[Results] We conducted an empirical study with data from “Hao Daifu (Great Doctors)”. The proposed algorithm could help patients find doctors meeting their needs.[Limitations] The patient’s decision-making history needs to be analyzed. Our recommendation algorithm is for a single patient, which is costly.[Conclusions] The proposed method could recommend appropriate doctors meeting patient’s needs.
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Ye Jiaxin,Xiong Huixiang,Jiang Wuxuan. A Physician Recommendation Algorithm Integrating Inquiries and Decisions of Patients. Data Analysis and Knowledge Discovery, 2020, 4(2/3): 153-164.
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