4.4 Article

Fuzzy constraint-based agent negotiation framework for doctor-patient shared decision-making

期刊

出版社

BMC
DOI: 10.1186/s12911-022-01963-x

关键词

Shared decision-making; Agent; Fuzzy constraint; Negotiation; Treatments recommendation

资金

  1. Science Foundation of Fujian Province [2021J011188]
  2. Xiamen Science and Technology Planning Project [3502Z20206073]
  3. Research Project of Xiamen Overseas Students [XRS202017206]
  4. Open Fund of Key Laboratory of Ecological Environment and Information Atlas, Fujian Provincial University [ST18004]
  5. Open Fund of Engineering Research Center of Big Data Application in Private Health Medicine, Fujian Provincial University [KF2020003]
  6. XMUT Scientific Research Project [YSK20002R, YKJCX2019108]

向作者/读者索取更多资源

This article introduces a fuzzy constraint-directed agent-based negotiation and recommendation framework for promoting shared decision-making (SDM) practice through intelligence. Experimental results show that the negotiation model effectively simulates preference negotiation and alleviates the pressure of increasing issues.
Background The clinical practice of shared decision-making (SDM) has grown in importance. However, most studies on SDM practice concentrated on providing auxiliary knowledge from the third-party standpoint without consideration for the value preferences of doctors and patients. The essences of these methods are complete and manual negotiation, and the problems of high cost, time consumption, delayed response, and decision fatigue are serious. Methods In response to the above limitations, this article proposes a fuzzy constraint-directed agent-based negotiation and recommendation framework for bilateral and multi-issue preference negotiation in SDM (PN-SDM). Its purpose is to provide preference information and intellectualize PN-SDM to promote SDM practice. We modeled PN-SDM problems as distributed fuzzy constraint satisfaction problems and designed the doctor agent and patient agent to negotiate on behalf of the doctor and patient. The negotiation result was then transformed into treatment plans by the recommendation model. The proposed negotiation and recommendation models were introduced in detail by an instance. Results The proposed method with different strategies and negotiation pairs achieves good performance in terms of negotiation running time, negotiation rounds, and combined aggregated satisfaction value. Specifically, it can feasibly and effectively complete multiple rounds of PN-SDM in a few seconds and obtain higher satisfaction. Conclusion The experimental results indicate that the negotiation model can effectively simulate preference negotiation and relieve the pressure of increasing issues. The recommendation model can assist in decision-making and help to realize SDM. In addition, it can flexibly cope with various negotiation scenarios by using different negotiation strategies (e.g., collaborative, win-win, and competitive).

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