Bridging Expertise: Doctor Recommendations for Cross-Disciplinary Collaborations in Online Medical Consultations

Online Medical Consultations (OMCs) are increasingly prevalent in Online Healthcare Communities (OHCs), with a considerable focus on doctor recommendations. However, existing research has predominantly centered on recommending individual specialized doctors, neglecting the exploration of more reliable interdisciplinary options for collaborative consultations. This paper introduces an innovative framework for interdisciplinary doctor recommendations for collaborative work in OMC scenarios, comprising two modules: one for calculating expertise and another for collaborative computing. Leveraging the medical knowledge graph, the former employs an expertise encoder to derive specialty embeddings for patient queries, doctor profiles, and historical consultations. The latter builds a collaborative circle for each doctor based on three dimensions: scientific citation, academic collaboration, and spatiotemporal proximity. This circle analysis delves into the potential for cooperation between doctors, aiming to identify optimal combinations. Experimental results on two real datasets demonstrate the superior performance of our proposed model compared to state-of-the-art methods. Ablation studies highlight the significant contribution of the three social network dimensions and their interactions to collaborative computing outcomes. Our model exhibits robustness across different parameter settings, as demonstrated through experiments. The study's results empower practitioners to develop a portfolio of recommendations, enhancing the effectiveness of cooperative consultations for complex diseases requiring multidisciplinary collaboration.