Published on in Vol 20, No 5 (2018): May

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/9160, first published .
Differences in Online Consumer Ratings of Health Care Providers Across Medical, Surgical, and Allied Health Specialties: Observational Study of 212,933 Providers

Differences in Online Consumer Ratings of Health Care Providers Across Medical, Surgical, and Allied Health Specialties: Observational Study of 212,933 Providers

Differences in Online Consumer Ratings of Health Care Providers Across Medical, Surgical, and Allied Health Specialties: Observational Study of 212,933 Providers

Journals

  1. Pruvis T, Holzman S, Hess D, Levin S, Maher D. Online Ratings of Pain Physicians in a Regional Population: What Matters?. Pain Medicine 2020;21(9):1743 View
  2. Khana R, Mahinderjit Singh M, Damanhoori F, Mustaffa N. Breast Self-Examination System Using Multifaceted Trustworthiness: Observational Study. JMIR Medical Informatics 2020;8(9):e21584 View
  3. Shandley L, Hipp H, Anderson-Bialis J, Anderson-Bialis D, Boulet S, McKenzie L, Kawwass J. Patient-centered care: factors associated with reporting a positive experience at United States fertility clinics. Fertility and Sterility 2020;113(4):797 View
  4. Haffey S, Hopman W, Leveridge M. Physicians' Earnings Do Not Affect Their Online Ratings. Frontiers in Public Health 2020;8 View
  5. 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
  6. Vorenkamp K, Sivanesan E. Determining Physician Quality in the Palm of Your Hand: Modern Convenience or Ploy?. Pain Medicine 2020;21(9):1741 View
  7. Rivas R, Montazeri N, Le N, Hristidis V. Automatic Classification of Online Doctor Reviews: Evaluation of Text Classifier Algorithms. Journal of Medical Internet Research 2018;20(11):e11141 View
  8. Rotman L, Alford E, Shank C, Dalgo C, Stetler W. Is There an Association Between Physician Review Websites and Press Ganey Survey Results in a Neurosurgical Outpatient Clinic?. World Neurosurgery 2019;132:e891 View
  9. Liu J, Zhang W, Jiang X, Zhou Y. Data Mining of the Reviews from Online Private Doctors. Telemedicine and e-Health 2020;26(9):1157 View
  10. Zillioux J, Pike C, Sharma D, Rapp D. Analysis of Online Urologist Ratings: Are Rating Differences Associated With Subspecialty?. Journal of Patient Experience 2020;7(6):1062 View
  11. Gong Y, Wang H, Xia Q, Zheng L, Shi Y. Factors that determine a Patient's willingness to physician selection in online healthcare communities: A trust theory perspective. Technology in Society 2021;64:101510 View
  12. Ye F, Ma D, Gong X, Yang Y, Chen Y. Development and validation of risk score for predicting spontaneous rupture of hepatocellular carcinoma. Annals of Surgical Treatment and Research 2020;99(5):268 View
  13. Zhao H, Luu M, Spiegel B, Daskivich T. Correlation of Online Physician Rating Subscores and Association With Overall Satisfaction: Observational Study of 212,933 Providers. Journal of Medical Internet Research 2020;22(10):e11258 View
  14. Raina R, Nair N, Sharma A, Chakraborty R, Rush S, Yap H, Sethi S, Bagga A, Hari P, Bunchman T, Bartosh S, Twombley K, Kapur G, McCulloch M, Filler G, Warady B, Díaz-González de Ferris M. Telemedicine for Pediatric Nephrology: Perspectives on COVID-19, Future Practices, and Work Flow Changes. Kidney Medicine 2021;3(3):412 View
  15. Anzer G, Bauer P. A Goal Scoring Probability Model for Shots Based on Synchronized Positional and Event Data in Football (Soccer). Frontiers in Sports and Active Living 2021;3 View
  16. Bae S, Lee J, Jeong J, Lim C, Choi J. Effective data-balancing methods for class-imbalanced genotoxicity datasets using machine learning algorithms and molecular fingerprints. Computational Toxicology 2021;20:100178 View
  17. Meister H, Valdez R, Martin D, Bulluck L. Predicting Pasture and Forest Landowner Intention to Create Early Successional Habitat. The Journal of Wildlife Management 2021;85(8):1656 View
  18. Ossai C, Bedrick S, Orwoll B. Using Publicly Available Reddit Data to Understand How Parents Choose Pediatricians. Journal of Consumer Health on the Internet 2022;26(2):186 View
  19. Chandrasekaran R, Bapat P, Jeripity Venkata P, Moustakas E. Do Patients Assess Physicians Differently in Video Visits as Compared with In-Person Visits? Insights from Text-Mining Online Physician Reviews. Telemedicine and e-Health 2023;29(10):1557 View
  20. McInturf A, Muhling B, Bizzarro J, Fangue N, Ebert D, Caillaud D, Dewar H. Spatial Distribution, Temporal Changes, and Knowledge Gaps in Basking Shark (Cetorhinus maximus) Sightings in the California Current Ecosystem. Frontiers in Marine Science 2022;9 View
  21. Islam S, Tahir M, Parveen S. GIS-based flood susceptibility mapping of the lower Bagmati basin in Bihar, using Shannon’s entropy model. Modeling Earth Systems and Environment 2022;8(3):3005 View
  22. Bernini A, Bosino A, Botha G, Maerker M. Evaluation of Gully Erosion Susceptibility Using a Maximum Entropy Model in the Upper Mkhomazi River Basin in South Africa. ISPRS International Journal of Geo-Information 2021;10(11):729 View
  23. Abaker M, Abdelmaboud A, Osman M, Alghobiri M, Abdelmotlab A. A Rock-fall Early Warning System Based on Logistic Regression Model. Intelligent Automation & Soft Computing 2021;28(3):843 View
  24. Xie Y, Xiang F. An improved approach based on dynamic mixed sampling and transfer learning for topic recognition: a case study on online patient reviews. Online Information Review 2022;46(6):1017 View
  25. Zaki P, Shenoy G, Gou J, Raj V, Howell K. Radiation Oncologist Perceptions and Utilization of Digital Patient Assessment Platforms. Applied Radiation Oncology 2020 View
  26. Riskiyadi M. Detecting future financial statement fraud using a machine learning model in Indonesia: a comparative study. Asian Review of Accounting 2023 View