936
Views
13
CrossRef citations to date
0
Altmetric
Original Articles

An adaptive doctor-recommender system

, , , & ORCID Icon
Pages 959-973 | Received 01 Mar 2018, Accepted 25 May 2019, Published online: 12 Jun 2019

References

  • Alluhaidan, A. 2013. “Recommender System Using Collaborative Filtering Algorithm.” School of Computing and Information Systems 10 (4): 155.
  • Andale. 2014. “Statistics How To.” Statistics How To, December 10. Accessed 25 September, 2017. http://www.statisticshowto.com/trimmed-mean/.
  • Badrul, S., G. Karypis, J. Konstan, and J. Riedl. 2001. Item-Based Collaborative Filtering Recommendation Algorithms. Minneapolis, MN and Hong Kong: Department of Computer Science and Engineering. 5545In WWW10
  • Balabanović, Marko. 1997. “An Adaptive Web Page Recommendation Service.” AGENTS ‘97 Proceedings of 1st International conference on Autonomous agents, 5–8 Feb, 378–385. doi:10.1145/267658.267744.
  • Best survey software. 2017. Accessed September 2, 2017. https://www.surveysystem.com/sscalc.htm.
  • Blue, J. and OPTUM Inc. 2018. Healthcare Similarity Engine. U.S. Patent Application 10/127,359.
  • Ceyhan, Migena, Z. Orhan, and E. Domnori. 2017. “e-Medical Test Recommendation System Based on the Analysis of Patients’ Symptoms and Anamneses.” Part of the IFMBE Proceedings book series (IFMBE, volume 62). March 15, 2017.
  • Chen, Min, Jun Yang, Yixue Hao, Shiwen Mao, and Kai Hwang. 2017. “A 5G Cognitive System for Healthcare.” Big Data and Cognitive Computing 1 (1): 2. doi: 10.3390/bdcc1010002
  • Cheung, K. L., D. Durusu, X. Sui, and H. de Vries. 2019. “How Recommender Systems Could Support and Enhance Computer-Tailored Digital Health Programs: A Scoping Review.” Digital Health 5. 2055207618824727. doi: 10.1177/2055207618824727
  • Duan, Lian, W. Nick Street, and Der-Fa Lu. 2008. “A Nursing Care Plan Recommended System Using a Data Mining Approach.” In Proceedings of the 3rd INFORMS Workshop on Data Mining and Health Informatics, edited by J. Li, D. Aleman, & R. Sikora, 1–6. Washington, DC.
  • Glover, Lacie. 2014. “Are Online Physician Ratings Any Good?” U.S.News, December 19. http://health.usnews.com/health-news/patient-advice/articles/2014/12/19/are-online-physician-ratings-any-good.
  • Guo, L., Bo Jin, Y. Cuili, Y. Haoyu, D. Huang, and F. Wang. 2017. “Which Doctorto Trust: A Recommender System for Identifying the Right Doctors.” Journal of Medical Internet Research. doi:10.2196/jmir.6015.
  • Haughom, John. 2016. “Knowledge Management in Healthcare: It’s More Important Than You Realize.” Health Catalyst, July. Accessed August 12, 2016. www.healthcatalyst.com/enable-knowledge-management-in-healthcare.
  • Hoens, T. Ryan, M. Blanton, and Nitesh V. Chawla. 2013. “Reliable Medical Recommendation Systems with Patient Privacy.” Journal of Medical Internet Research 4: 67.
  • Huang, Y., P. Liu, Q. Pan, and J. S. Lin. 2012. “A Doctor Recommendation Algorithm Based on Doctor Performances and Patient Preferences.” In Proceedings of the Wavelet Active Media Technology and Information Processing. doi:10.1109/ICWAMTIP.2012.6413447.
  • Hussein, Asmaa S., Wail M. Omar, Xue Li, and Modafar Ati. 2013. “Efficient Chronic Disease Diagnosis Prediction and Recommendation System.” Biomedical Engineering and Sciences (IECBES). doi:10.1109/IECBES.2012.6498117.
  • Investopedia. 2016. Accessed 12 August, 2016. www.investopedia.com/terms/w/weightedaverage.asp.
  • Kaur, Harmanjeet, Neeraj Kumar, and Shalini Batra. 2018. “An Efficient Multi-Party Scheme for Privacy Preserving Collaborative Filtering for Healthcare Recommender System.” Future Generation Computer Systems 86: 297–307. doi: 10.1016/j.future.2018.03.017
  • Lamber, P., A. Girardello, F. Ricci, and M. Mitterer. 2009. “MobiDay: Apersonalized Context-Aware Mobile Service for Day Hospital Workflow Support.” In Proceeding of the AIME09 International Workshop on Personalization for e-Health, 15–19. Italy: Proceedings of the AIME09 International Workshop.
  • Masood, Isma, Yongli Wang, Ali Daud, Naif Radi Aljohani, and Hassan Dawood. 2018. “Privacy Management of Patient Physiological Parameters.” Telematics and Informatics 35 (4): 677–701. doi: 10.1016/j.tele.2017.12.020
  • Melville, P., and V. Sindhwani. 2013. Recommender Systems. Yorktown Heights, NY: IBM T.J. Watson Research Center. [email protected].
  • Mika, Stefanie. 2011. Challenges for Nutrition Recommender Systems. Erlangen: Department of Computer Science, 8 Friedrich-Alexander-University Erlangen-Nuremberg Haberstraße 2, D-91058.
  • Narducci, F., C. Musto, M. Polignano, M. de Gemmis, P. Lops, and G. Semeraro. 2015. “A Recommender System for Connecting Patients to the Right Doctors in the Health Net Social Network.” In Proceedings of the 24th International Conference on World Wide Web, 81–82. doi:10.1145/2740908.2742748.
  • Park, D. H., H. K. Kim, I. Y. Choi, and J. K. Kim. 2012. “A Literature Review and Classification of Recommender Systems Research.” Expert Systems with Applications 39 (11): 10059–10072. doi: 10.1016/j.eswa.2012.02.038
  • Portugal, Ivens, Paulo Alencar, and Donald Cowan. 2018. “The Use of Machine Learning Algorithms in Recommender Systems: A Systematic Review.” Expert Systems with Applications 97: 205–227. doi: 10.1016/j.eswa.2017.12.020
  • Qian, Y., Y. Zhang, X. Ma, H. Yu, and L. Peng. 2019. “EARS: Emotion-Aware Recommender System Based on Hybrid Information Fusion.” Information Fusion 46: 141–146. doi: 10.1016/j.inffus.2018.06.004
  • Rawat, Bhupesh, and Sanjay K. Dwivedi. 2019. “Selecting Appropriate Metrics for Evaluation of Recommender Systems.” InternationalJournal of Information Technology and Computer Science 1: 14–23. doi: 10.5815/ijitcs.2019.01.02
  • Saaty, Thomas L. 2013. “Analytic Hierarchy Process.” In Encyclopedia of Operations Research and Management Science, 52–64. Boston, MA: Springer.
  • Safoury, L., and A. Salah. 2013. “Exploiting User Demographic Attributes for Solving Cold-Start Problem in Recommender System.” Lecture Notes on Software Engineering 1 (3): 303–307. doi: 10.7763/LNSE.2013.V1.66
  • Salunke, Archana, B. and Kasar, and L. Smita. 2015. “Personalized Recommendation System for Medical Assistance Using Hybrid Filtering.” International Journal of Computer Applications 128 (9): 6–10. doi: 10.5120/ijca2015906626
  • Schafer, H., S. Hor-Fraile, and R. Pawan. 2017. “Towards Health (Aware) Recommender Systems.” In Proceedings of dh’17, 157–161. London: Proceedings of the 2017 international conference on digital health ACM.
  • Stockemer, Daniel. 2019. “Conducting a Survey.” In Quantitative Methods for the Social Sciences, 57–71. Cham: Springer.
  • Tabari, Mahdiyeh Yousefi, and Azizollah Memariani. 2019. “Developing a Decision Support System for Big Data Analysis and Cost Allocation in National Healthcare.” In Healthcare Data Analytics and Management, 89–109. Academic Press.
  • Wiesner, Martin, and Daniel Pfeifer. 2010. “Adapting Recommender Systems to the Requirements of Personal Health Record Systems.” In Proceedings of the 1st ACM International Health Informatics Symposium, 410–414. doi:10.1145/1882992.1883053.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.