This paper is in the following e-collection/theme issue:

Physician and Health Services Rating by Consumers (128)

Published on in Vol 18, No 7 (2016): July

Which Doctor to Trust: A Recommender System for Identifying the Right Doctors

Which Doctor to Trust: A Recommender System for Identifying the Right Doctors

Which Doctor to Trust: A Recommender System for Identifying the Right Doctors

Authors of this article:

Li Guo1 Author Orcid Image ;   Bo Jin1, 2 Author Orcid Image ;   Cuili Yao2 Author Orcid Image ;   Haoyu Yang2 Author Orcid Image ;   Degen Huang1 Author Orcid Image ;   Fei Wang3 Author Orcid Image
Article Authors Cited by (34) Tweetations (36) Metrics

Journals

  1. Mondal S, Basu A, Mukherjee N. Building a trust-based doctor recommendation system on top of multilayer graph database. Journal of Biomedical Informatics 2020;110:103549 View
  2. Cheung K, Durusu D, Sui X, de Vries H. How recommender systems could support and enhance computer-tailored digital health programs: A scoping review. DIGITAL HEALTH 2019;5 View
  3. Sharma D, Singh Aujla G, Bajaj R. Evolution from ancient medication to human‐centered Healthcare 4.0: A review on health care recommender systems. International Journal of Communication Systems 2023;36(12) View
  4. Hors-Fraile S, Rivera-Romero O, Schneider F, Fernandez-Luque L, Luna-Perejon F, Civit-Balcells A, de Vries H. Analyzing recommender systems for health promotion using a multidisciplinary taxonomy: A scoping review. International Journal of Medical Informatics 2018;114:143 View
  5. Xu Y, Zhou D, Ma J. Scholar-friend recommendation in online academic communities: An approach based on heterogeneous network. Decision Support Systems 2019;119:1 View
  6. Cheshire W. Autonomic medical practice viewed through the lens of physician-rating websites. Clinical Autonomic Research 2020;30(4):335 View
  7. Hong Y, Liang C, Radcliff T, Wigfall L, Street R. What Do Patients Say About Doctors Online? A Systematic Review of Studies on Patient Online Reviews. Journal of Medical Internet Research 2019;21(4):e12521 View
  8. Sharma D, Singh Aujla G, Bajaj R. Deep neuro‐fuzzy approach for risk and severity prediction using recommendation systems in connected health care. Transactions on Emerging Telecommunications Technologies 2021;32(7) View
  9. Yuan H, Deng W. Doctor recommendation on healthcare consultation platforms: an integrated framework of knowledge graph and deep learning. Internet Research 2022;32(2):454 View
  10. De Croon R, Van Houdt L, Htun N, Štiglic G, Vanden Abeele V, Verbert K. Health Recommender Systems: Systematic Review. Journal of Medical Internet Research 2021;23(6):e18035 View
  11. Etemadi M, Bazzaz Abkenar S, Ahmadzadeh A, Haghi Kashani M, Asghari P, Akbari M, Mahdipour E. A systematic review of healthcare recommender systems: Open issues, challenges, and techniques. Expert Systems with Applications 2023;213:118823 View
  12. Liu J, Li C, Huang Y, Han J. An intelligent medical guidance and recommendation model driven by patient-physician communication data. Frontiers in Public Health 2023;11 View
  13. Sajde M, Malek H, Mohsenzadeh M. RecoMed: A knowledge-aware recommender system for hypertension medications. Informatics in Medicine Unlocked 2022;30:100950 View
  14. Shah A, Muhammad W, Lee K, Naqvi R. Examining Different Factors in Web-Based Patients’ Decision-Making Process: Systematic Review on Digital Platforms for Clinical Decision Support System. International Journal of Environmental Research and Public Health 2021;18(21):11226 View
  15. Sun Y, Zhou J, Ji M, Pei L, Wang Z. Development and Evaluation of Health Recommender Systems: Systematic Scoping Review and Evidence Mapping. Journal of Medical Internet Research 2023;25:e38184 View
  16. Wu J, Zhang G, Xing Y, Liu Y, Zhang Z, Dong Y, Herrera-Viedma E. A sentiment analysis driven method based on public and personal preferences with correlated attributes to select online doctors. Applied Intelligence 2023;53(16):19093 View
  17. Lu W, Zhai Y. Self-Adaptive Telemedicine Specialist Recommendation Considering Specialist Activity and Patient Feedback. International Journal of Environmental Research and Public Health 2022;19(9):5594 View
  18. Slade E, Rennick-Egglestone S, Ng F, Kotera Y, Llewellyn-Beardsley J, Newby C, Glover T, Keppens J, Slade M. The Implementation of Recommender Systems for Mental Health Recovery Narratives: Evaluation of Use and Performance. JMIR Mental Health 2024;11:e45754 View
  19. Liu X, Guo H, Wang L, Hu M, Wei Y, Liu F, Wang X. Effect of Prosocial Behaviors on e-Consultations in a Web-Based Health Care Community: Panel Data Analysis. Journal of Medical Internet Research 2024;26:e52646 View
  20. Jiang H, Mi Z, Xu W. Online Medical Consultation Service–Oriented Recommendations: Systematic Review. Journal of Medical Internet Research 2024;26:e46073 View
  21. António J, Malheiro R, Jardim S. Feedback Collection and Nearest-Neighbor Profiling for Recommendation Systems in Healthcare Scenarios. Technologies 2024;12(8):127 View
  22. Gao Q, Wang X, Lin Z, Liao Z. Internet usage time and trust in doctors: evidence from China. BMC Public Health 2024;24(1) View
  23. Lin Q, Chen X, Yang S, Wang D. What information do patients pay more attention to in online physician selection? Information needs model for online medical choice decision-making based on trust theory and fuzzy decision. International Journal of Medical Informatics 2025;195:105723 View

Books/Policy Documents

  1. Iftikhar H, Anwar S, Majid M. Intelligent Technologies and Applications. View
  2. Peito J, Han Q. Complex Networks & Their Applications IX. View
  3. Lamba D, Hsu W, Alsadhan M. Machine Learning, Big Data, and IoT for Medical Informatics. View
  4. Parisa Begum K, Sheen S. Computational Intelligence, Cyber Security and Computational Models. Recent Trends in Computational Models, Intelligent and Secure Systems. View