Patient-centered doctor recommender system of online health communities: A multidimensional sequence alignment approach

• Published in: International journal of information management 2025-04, Vol.81, p.102865, Article 102865
• Main Authors: Meng, Xue, Zhang, Jianghua, Fu, Xuemei
• Format: Article
• Language: English
• Subjects: Doctor recommender system; Multidimensional sequence alignment; Online health communities; Opinion mining; Patient-centered
• ISSN: 0268-4012
• DOI: 10.1016/j.ijinfomgt.2024.102865

This study develops a patient-centered Doctor Recommender System (DRS), facilitating patients' doctor choice performance by calculating doctors' "biological distance" based on Multidimensional Sequence Alignment (MSA) method. The distance is measured by doctor-patient interaction attributes, which are acquired from a combination of Levenshtein Distance and opinion mining technology. The XGBoost is used to identify the importance of these attributes. The precision of patient-centered DRS is 72.60 %, and the recommended doctors are significantly different from the doctors chosen by patients lacking medical knowledge. It not only furnishes practical guidance for OHCs in increasing patients' consulting satisfaction, but also illuminates the important properties in improving doctors' popularity. •A patient-centered Doctor Recommender System of OHCs is developed.•Multidimensional Sequence Alignment is used to obtain doctors' biological distance.•Distance between doctors is measured using doctor-patient interaction attributes.•The results are useful for OHCs in increasing patients’ consulting satisfaction.