面向在线问诊平台的医生推荐方法及应用研究综述

doi:10.11896/jsjkx.240600149

摘要/Abstract

摘要： 文章旨在强化个性化推荐技术在互联网医疗场景下的应用,辅助患者选择优质的医生资源,解决在线问诊规模不断扩大带来的信息过载问题。通过文献计量归纳热门研究方向,系统梳理现有在线医生推荐模式。根据医患匹配原理,将现有模式划分为5类:基于传统推荐算法的推荐模式、基于多属性决策的推荐模式、基于机器学习的推荐模式、混合推荐模式,以及其他推荐模式。对比各模式的应用现状、优缺点及适用范围,分析发展趋势并提出未来研究方向。在线医生推荐属于计算机科学、管理学及医学领域的交叉研究问题,相较于传统的推荐系统,它更侧重于对患者病情与医生专业领域的精准匹配。传统推荐算法在在线医生推荐领域应用较早,但受限于数据稀疏性与冷启动问题。基于多属性决策的推荐模式理论扎实,能灵活反映患者偏好,但对系统与患者间的交互需求高。基于机器学习的推荐模式能缓解数据稀疏难题,实现智能推荐,但需大量数据支持且欠缺可解释性。混合推荐模式通过整合多种算法优势,有望提升推荐效率与精准度,然而,如何有效组合与平衡各算法成为关键挑战。此外,基于优化理论与图模型等的推荐模式尚待深入研究。未来还需融合多学科理论方法,对跨平台多源异构型医患数据的挖掘、表达、整合进行研究,探索基于患者个性化需求及偏好的医生推荐模式。

关键词: 在线问诊, 医生推荐, 推荐算法, 机器学习, 多属性决策

Abstract: This paper aims to strengthen the use of personalized recommendation technologies in online medical settings,help patients choose resources for high-quality physicians,and address the information overload caused by the growing volume of online consultations.Firstly,bibliometrics summarizes popular research directions.On this basis,this paper sorts out the existing online doctor recommendation methods and classifies them into five categories based on doctor-patient matching:recommendation based on traditional recommendation algorithms,recommendation based on multi-attribute decision making,recommendation based on machine learning,hybrid recommendation,and others.In addition,we compare the application status,advantages and disadvantages,and the application scope of each category.Finally,we analyze the trend of online doctor recommendations and propose future research directions.Online doctor recommendation belongs to the intersection of research problems in the fields of computer science,management,and medicine.In contrast to traditional recommender systems,online doctor recommendation prioritizes precise matching between patients' conditions and doctors' specialties.Traditional recommendation algorithms are initially applied in doctor recommendation,but they are constrained by data sparsity and cold start.Recommendation based on multi-attribute decision making possess a solid theoretical foundation and can flexibly reflect patient preferences,yet they require a high level of interaction between the system and patients.Recommendation based on machine learning can alleviate the challenge of data sparsity and enable intelligent recommendation,though they necessitate large data support and often suffer from poor interpre-tability.Hybrid recommendation models,by integrating the strengths of various algorithms,have the potential to improve recommendation performance.However,the challenge lies in combining and balancing these algorithms.Other research directions such as recommendation grounded in optimization theory and graph models remain to be explored.In the future,it will be important to integrate multidisciplinary methodologies,conduct research on cross-platform,multi-source,and heterogeneous doctor-patient data mining,expression,and integration,and explore doctor recommendation modes based on patients' needs and preferences.

Key words: Online consultation, Doctor recommendation, Recommendation algorithm, Machine learning, Multi-attribute decision making

中图分类号:

C934

吴性丽, 张皓月, 廖虎昌. 面向在线问诊平台的医生推荐方法及应用研究综述[J]. 计算机科学, 2025, 52(5): 109-121. https://doi.org/10.11896/jsjkx.240600149

WU Xingli, ZHANG Haoyue, LIAO Huchang. Review of Doctor Recommendation Methods and Applications for Consultation Platforms[J]. Computer Science, 2025, 52(5): 109-121. https://doi.org/10.11896/jsjkx.240600149

参考文献

[1]CHEN Y W,LEE S.User-generated physician ratings and their effects on patients' physician choices:Evidence from Yelp[J].Journal of Marketing,2024,88(1):77-96.
[2]HONG Y A,LIANG C,RADCLIFF T A,et al.What do pa-tients say about doctors online? A systematic review of studies on patient online reviews[J].Journal of Medical Internet Research,2019,21(4):e12521.
[3]DARAZ L,MORROW A S,PONCE O J,et al.Can patientstrust online health information? A meta-narrative systematic review addressing the quality of health information on the internet[J].Journal of General Internal Medicine,2019,34(9):1884-1891.
[4]PLACONA A M,RATHERT C.Are online patient reviews associated with health care outcomes? A systematic review of the literature[J].Medical Care Research and Review,2022,79(1):3-16.
[5]LI A,NING N,LIN S Y.Brief analysis of domestic research on medical service online reviews[J].Foreign Economic Relations Trade,2020,3:32-43.
[6]HAN X.Review and future directions of research on online reviews of physicians[J].Journal of Modern Information,2019,39(11):146-158.
[7]LIAO H C,LIU F,LU K Y,et al.Online medical reviews on patient behavior mining and it applications in medical decision-making and management[J].Journal of UESTC(Social Sciences Edition),2022,24(3):1-22.
[8]WU J,LIU G J,HU X.An overview of online medical andhealth research:hot topics,theme evolution and research content[J].Data Analysis and Knowledge Discovery,2019(4):2-12.
[9]SHANG LL,ZUO M Y,MA D,et al.The antecedents and consequences of health care professional-patient online interactions:Systematic review[J].Journal of Medical Internet Research,2019,21(9):e13940.
[10]SHEN X Y,CAI X H,CAO H.Research progress of recommendation system based on medical knowledge graph[J].Computer Engineering and Applications,2023,59(19):40-51.
[11]HU J H,ZHANG X H,YANG Y,et al.New doctors ranking system based on VIKOR method[J].International Transactions in Operational Research,2020,27(2):1236-1261.
[12]ZADEH L A.Fuzzy sets[J].Information and Control,1965,8(3):338-353.
[13]ADOMAVICIUS G,TUZHILIN A.Toward the next generation of recommender systems:A survey of the state-of-the-art and possible extensions[J].IEEE Transactions on Knowledge and Data Engineering,2005,17(6):734-749.
[14]GUO L,JIN B,YAO C L,et al.Which doctor to trust:a recommender system for identifying the right doctors[J].Journal of Medical Internet Research,2016,18(7):e6015.
[15]HOU M W,WEI R,WANG T G,et al.Reliable medical recommendation based on privacy-preserving collaborative filtering[J].Computers,Materials & Continua,2018,56(1):137-149.
[16]LI D B,CHEN X Q,CHEN S P.Learning and optimization of patient-physician matching index in specialty care[J].IEEE Transactions on Automation Science and Engineering,2024,21(3):2730-2741.
[17]LU W,ZHAI Y K.Self-adaptive telemedicine specialist recommendation considering specialist activity and patient feedback[J].International Journal of Environmental Research and Public Health,2022,19(9):5594.
[18]LU W,GAO P,ZHAI K Y.An adaptive recommendation method for telemedicine specialists with feedback adjustment[J].Journal of Systems& Management.2023,32(5):960-975.
[19]GAO S,LIU W,CUI Y,et al.Collaborative filtering algorithm integrating multiple user behaviors[J].Computer Science,2016,43(9):227-231.
[20]XIONG H X,LI X M,LI J L.Research on online doctor recommendation based on doctor-patient interaction data[J].Information Studies:Theory＆Application,2020,43(8):159-166.
[21]NING J F,HUANG F L.Measuring sentence similarity basedon word vector for medical department recommendation[J].Journal of Fujian Normal University(Natural Science Edition),2018(4):10-15.
[22]LIU T.An application research of automatic physician matching algorithm based on online healthcare consultation records[J].Information Studies:Theory＆Application,2018,41(6):143-148.
[23]PAN X,WEN H Q,WANG Z W,et al.Physician ranking optimization based on patients′ browse behaviors and resource capacities[J].Internet Research,2021,31(6):2076-2095.
[24]WANG H,DING S,LI Y Q,et al.Hierarchical physician recommendation via diversity-enhanced matrix factorization[J].ACM Transactions on Knowledge Discovery from Data(TKDD),2020,15(1):1-17.
[25]WU J W,SUN Y X.Recommendation system for medical consultation integrating knowledge graph and deep learning methods[J].Journal of Frontiers of Computer Science and Technology,2021,15(8):1432-1440.
[26]HU J H,PAN L,CHEN X H.An intervalneutrosophic projec-tion-based VIKOR method for selecting doctors[J].Cognitive Computation,2017,9:801-816.
[27]DU Y F,CHEN Z S,YANG J,et al.A textual data-orientedmethod for doctor selection in online health communities[J].Sustainability,2023,15(2):1241.
[28]CHEN J Y,LI X H.Doctors ranking through heterogeneous information:The new score functions considering patients' emotional intensity[J].Expert Systems with Applications,2023,219:119620.
[29]TANG G L,ZHANG X Y,ZHU B Y,et al.A mathematical programming method based on prospect theory for online physician selection under an R-set environment[J].Information Fusion,2023,93:441-468.
[30]YANG Y,HU J,LIU Y,et al.Doctor recommendation based on an intuitionistic normal cloud model considering patient preferences[J].Cognitive Computation,2020,12:460-478.
[31]CHEN X H,WANG H,LI X H.Doctor recommendation under probabilistic linguistic environment considering patient's risk preference[J].Annals of Operations Research,2024,341:555-581.
[32]LIU F,LIAO H C,AL-BARAKATI A.Physician selectionbased on user-generated content considering interactive criteria and risk preferences of patients[J].Omega,2023,115:102784.
[33]LI H.An Extended TOPSIS-based doctor recommendationmethod based on unbalanced linguistic term sets[J].Fuzzy Systems and Mathematics,2023,37(4):81-91.
[34]YAN Y J,YU G,YAN X B.Online doctor recommendation with convolutional neural network and sparse inputs[J].Computational Intelligence and Neuroscience,2020,2020:10.
[35]NIE H,CAI R S.The online doctor recommendation system using attention mechanism[J].Data Analysis and Knowledge Discovery,2023,7(8):138-148.
[36]DU G,HUANG L Y,XU X J.Research on the medical recommendation model considering patient preference diversity with persistent use behavior[J].Journal of Systems & Management,2024,33(3):667-685.
[37]YE Y,ZHAO Y,SHANG J,et al.A hybrid IT framework for identifying high-quality physicians using big data analytics[J].International Journal of Information Management,2019,47:65-75.
[38]LIU J S,LI C R,HUANG Y,et al.An intelligent medical guidance and recommendation model driven by patient-physician communication data[J].Frontiers in Public Health,2023,11:1098206.
[39]YE J X,XIONG H X,JIANG W X.A physician recommendation algorithm integrating inquiries and decisions of patients[J].Data Analysis and Knowledge Discovery,2020,4(2/3):153-164.
[40]LI Y Y,XIONG H X,LI X M.Recommending doctors onlinebased on combined conditions[J].Data Analysis and Knowledge Disco-very,2020,4(8):130-142.
[41]LIANG J S,YE X Q,LIU D.Three-way recommendations for online medical consultation platform[J].Journal of Northwest University(Natural Science Edition),2022,52(5):784-796.
[42]ZHOU X K,LI Y,LIANG W.CNN-RNN based intelligent recommendation for online medical pre-diagnosis support[J].IEEE/ACM Transactions on Computational Biology and Bioinformatics,2020,18(3):912-921.
[43]PAN Y N,NI X L.Recommending online medical experts with Labeled-LDA model[J].Data Analysis and Knowledge Disco-very,2020,4(4):34-43.
[44]MENG Q Q,XIONG H X.Doctor recommendation based on online consultation text information[J].Information Science,2021,39(6):152-160.
[45]JU C H,ZHANG S Z.Doctor recommendation model based on ontology characteristics and disease text mining perspective[J].BioMed Research International,2021,2021:1-12.
[46]LIANG P,HU J H,CHIN K S.A comprehensive decision support model for online doctors ranking with interval-valuedneutrosophic numbers[J].International Transactions in Operational Research,2024,31(4):2504-2527.
[47]WANG M W,LIANG D C,CAO W,et al.Physician recommendation via online and offline social network group decision ma-king with cross-network uncertain trust propagation[J/OL].https://doi.org/10.1007/s10479-022-04827-9.
[48]WU J,ZHANG G Y,XING Y M,et al.A sentiment analysisdriven method based on public and personal preferences with correlated attributes to select online doctors[J].Applied Intelligence,2023,53(16):19093-19114.
[49]ZHOU X,XIONG H X,XIAO B.A physician recommendation algorithm based on the fusion of label and patient consultation text[J].Information Science,2023,41(3):145-154.
[50]WANG R J,WANG J M.Research on doctor recommendation of online “ask the doctor” platforms based on the perspective of users recognition[J].Library and Information Service,2023,67(10):128-138.
[51]ZHANG Y,CHEN M,HUANG D J,et al.iDoctor:Personalized and professionalized medical recommendations based on hybrid matrix factorization[J].Future Generation Computer Systems,2017,66:30-35.
[52]LI X H,LUO Y,WANG H,et al.Doctor selection based on aspect-based sentiment analysis andneutrosophic TOPSIS method[J].Engineering Applications of Artificial Intelligence,2023,124:106599.
[53]SUN R X,HU J H,CHEN X H.Novel single-valuedneutro-sophic decision-making approaches based on prospect theory and their applications in physician selection[J].Soft Computing,2019,23:211-225.
[54]RANI P,MISHRA A R,PARDASANI K R.A novel WASPAS approach for multi-criteria physician selection problem with intuitionistic fuzzy type-2 sets[J].Soft Computing,2020,24:2355-2367.
[55]ZHAI S S,HU P,PAN Y Z,et al.Scenario-based informationrecommendation of online medical community based on knowledge graph and disease portrait[J].Information Science,2021,39(5):97-105.
[56]WANG R J,ZHANG L,WANG J M.Automatic triage of online doctor services based on machine learning[J].Data Analysis and Knowledge Discovery,2019,3(9):88-97.
[57]ZHANG M,SUN B Z,WANG T,et al.Multi-criteria three-way recommendation of heterogeneous information based on rough set and GRA and its application in medical recommendation[J].Control and Decision,2022,37(7):1883-1893.
[58]GONG J B,CHENG H,WANG L L.Individual doctor recom-mendation in large networks by constrained optimization[J].International Journal of Web Services Research(IJWSR),2015,12(4):16-28.
[59]SANGAIAH A K,REZAEI S,JAVADPOUR A,et al.Explainable AI in big data intelligence of community detection for digitalization e-healthcare services[J].Applied Soft Computing,2023,136:110119.
[60]YUAN H,DENG W W.Doctor recommendation on healthcare consultation platforms:an integrated framework of knowledge graph and deep learning[J].Internet Research,2022,32(2):454-476.
[61]MA Y,ZHANG Y,WANG Z H,et al.A personalized recommendation algorithm for intelligent guidance[J].CAAI transactions on intelligent systems,2018,13(3):352-358.
[62]SARUCAN A,BAYSAL M E,ENGIN O.A spherical fuzzy TOPSIS method for solving the physician selection problem[J].Journal of Intelligent & Fuzzy Systems,2022,42(1):181-194.
[63]WEN H Q,SONG J,PAN X.Physician recommendation onhealthcare appointment platforms considering patient choice[J].IEEE Transactions on Automation Science and Engineering,2019,17(2):886-899.
[64]PAN X,SONG J,ZHANG F.Dynamic recommendation of physician assortment with patient preference learning[J].IEEE Transactions on Automation Science and Engineering,2018,16(1):115-126.
[65]GONG J B,WANG L L,SUN S T,et al.iBole:a hybrid multi-layer architecture for doctor recommendation in medical social networks[J].Journal of Computer Science and Technology,2015,30:1073-1081.
[66]TANG X B,GAO H X.Study of the doctor portrait based on feature analysis and label extraction[J].Information Science,2020,38(5):3-10.
[67]XIA S D,DENG S L,QIAN Q W,et al.Analysis ofonline medical community physician group division and characteristic from perspective of value co-creation[J].Journal of Modern Information,2024,44(2):92-106.
[68]MENG Q Q,XIONG H X,TONG Z L,et al.Automatic generation of doctor label based on online consultation text information[J].Information Science,2020,38(5):58-64.
[69]NIE H,WU X Y,LIN Y.Clustering and characterizing depression patients based on online medical records[J].Data Analysis and Knowledge Discovery,2022,6:222-232.
[70]XU S K,WU WW.Balance recommendation algorithm for medical resources based on semantic[J].Computer Engineering,2015,41(9):74-79.
[71]REN Z Y,PENG B,SCHLEYER T K,et al.Hybrid collaborative filtering methods for recommending search terms to clinicians[J].Journal of Biomedical Informatics,2021,113:103635.
[72]MONDAL S,BASU A,MUKHERJEE N.Building a trust-based doctor recommendation system on top of multilayer graph database[J].Journal of Biomedical Informatics,2020,110:15.
[73]MANI V,THILAGAMANI S.Hybrid filtering-based physician recommender systems using fuzzy analytic hierarchy process and user ratings[J].International Journal of Computers Communications & Control,2023,18(6):1-17.
[74]WAQAR M,MAJEED N,DAWOOD H,et al.An adaptive doctor-recommender system[J].Behaviour & Information Techno-logy,2019,38(9):959-973.
[75]CHANG W J,ZHANG Q,FU C,et al.A cross-domain recommender system through information transfer for medical diagnosis[J].Decision Support Systems,2021,143:113489.
[76]WANG G X,LIU H P.Survey of personalized recommendation system[J].Computer Engineering and Applications,2012,4(7):66-76.
[77]XU H L,WU X,LI X D,et al.Comparison study of Internet recommendation system[J].Journal of Software,2009,20(2):350-362.
[78]YANG B,ZHAO P F.Review of the art of recommendation algorithms[J].Journal of Shanxi University(Natural Science Edition),2011,34(3):337-350.
[79]GRÄßER F,TESCH F,SCHMITT J,et al.A pharmaceuticaltherapy recommender system enabling shared decision-making[J].User Modeling and User-Adapted Interaction,2022,32:1019-1062.
[80]WANG J S,ZHANG G M,HU B.A survey of deep learning based recommendation algorithms[J].Journal of Nanjing Normal University(Engineering And Technology Edition),2018,18(4):33-43.
[81]ZHOU Y,LEI S Y,ZHANG C.An improved recommendation algorithm for mobile health care system[J].Journal of University of Chinese Academy of Sciences,2017,34(1):112-118.
[82]CHEN J G,LI K L,RONG H G,et al.A disease diagnosis and treatment recommendation system based on big data mining and cloud computing[J].Information Sciences,2018,435:124-149.
[83]BURKE R.Knowledge-based recommender systems[J].Ency-clopedia of Library and Information Systems,2000,69:175-186.
[84]KIM J,LEE D,CHUNG K Y.Item recommendation based on context-aware model for personalized u-healthcare service[J].Multimedia Tools and Applications,2014,71:855-872.
[85]ZHANG D,HU J H.A novel multi-interval-valued fuzzy setmodel to solve MADM problems[J].Expert Systems with Applications,2024,238:122248.
[86]LI P F,LU F M,BAO Y X,et al.Drug recommendation method based on medical process mining and patient signs[J].Computer Integrated Manufacturing Systems,2020,26(6):1668-1678.
[87]KUMAR A,AIKENS R C,HOM J,et al.OrderRex clinical user testing:a randomized trial of recommender system decision support on simulated cases[J].Journal of the American Medical Informatics Association,2020,27(12):1850-1859.
[88]TIAN B,ZHANG Y,CHEN X H,et al.DRGAN:A GAN-based framework for doctor recommendation in Chinese on-line QA communities[C]//Database Systems for Advanced Applications:DASFAA 2019 International Workshops:BDMS,BDQM,and GDMA,Chiang Mai,Thailand,April 22-25,2019,Procee-dings 24.Springer International Publishing,2019:444-447.
[89]ZHENG Z,QIU Z P,XIONG H,et al.DDR:Dialogue based doctor recommendation for online medical service[C]//Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining.2022:4592-4600.
[90]WANG Y,GE S,ZHAO X Y,et al.Doctor specific tag recommendation for online medical record management[C]//Procee-dings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining.2023:5150-5161.
[91]LI Y R,SHI Y L,JIN Y D,et al.A collaborative cross-attention drug recommendation model based on patient and medical relationship representations[C]//2023 IEEE International Confe-rence on Bioinformatics and Biomedicine(BIBM).IEEE,2023:2036-2039.
[92]HAN Q W,JI M X,DE TROYA I M R,et al.A hybrid recommender system for patient-doctor matchmaking in primary care[C]//2018 IEEE 5th International Conference on Data Science and Advanced Analytics(DSAA).IEEE,2018:481-490.
[93]XU Z S,CHEN H Y,HE Y.A recommender system based on hesitant fuzzy linguistic information with MAPPACC approach[J].Studies in Informatics and Control,2020,29(2):145-158.
[94]LIU M,LIU Z,XIAO L,et al.A study of medical decision re-commendation generation and similarity fusion based on CDSS and ChatGPT-4[C]//2023 IEEE International Conference on Bioinformatics and Biomedicine(BIBM).2023:873-878.
[95]LIANG P,HU J H,LI B,et al.A group decision making with probability linguistic preference relations based on nonlinear optimization model and fuzzy cooperative games[J].Fuzzy Optimization and Decision Making,2020,19:499-528.
[96]DU J Z,GAO S Y,CHEN C H.A contextual ranking and selection method for personalized medicine[J].Manufacturing & Service Operations Management,2024,26(1):167-181.

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