Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/16848, first published .
Development, Implementation, and Evaluation of a Personalized Machine Learning Algorithm for Clinical Decision Support: Case Study With Shingles Vaccination

Development, Implementation, and Evaluation of a Personalized Machine Learning Algorithm for Clinical Decision Support: Case Study With Shingles Vaccination

Development, Implementation, and Evaluation of a Personalized Machine Learning Algorithm for Clinical Decision Support: Case Study With Shingles Vaccination

Journals

  1. Wan P, Satybaldy A, Huang L, Holtskog H, Nowostawski M. Reducing Alert Fatigue by Sharing Low-Level Alerts With Patients and Enhancing Collaborative Decision Making Using Blockchain Technology: Scoping Review and Proposed Framework (MedAlert). Journal of Medical Internet Research 2020;22(10):e22013 View
  2. Kim K, Yang H, Yi J, Son H, Ryu J, Kim Y, Jeong J, Chin H, Na K, Chae D, Han S, Kim S. Real-Time Clinical Decision Support Based on Recurrent Neural Networks for In-Hospital Acute Kidney Injury: External Validation and Model Interpretation. Journal of Medical Internet Research 2021;23(4):e24120 View
  3. Baron J, Huang R, McEvoy D, Dighe A. Use of machine learning to predict clinical decision support compliance, reduce alert burden, and evaluate duplicate laboratory test ordering alerts. JAMIA Open 2021;4(1) View
  4. Mehta N, Born K, Fine B. How artificial intelligence can help us ‘Choose Wisely’. Bioelectronic Medicine 2021;7(1) View
  5. Ozaydin B, Berner E, Cimino J. Appropriate use of machine learning in healthcare. Intelligence-Based Medicine 2021;5:100041 View
  6. Hui Z, Jun B, Na Z, Fan Y. Automatic Recognition Method of Fall Movement of Sports Fitness Human Body Based on Posture Data Sequence. Journal of Sensors 2022;2022:1 View
  7. Kashyap S, Morse K, Patel B, Shah N. A survey of extant organizational and computational setups for deploying predictive models in health systems. Journal of the American Medical Informatics Association 2021;28(11):2445 View
  8. Chandeying N, Thongseiratch T. Systematic review and meta-analysis comparing educational and reminder digital interventions for promoting HPV vaccination uptake. npj Digital Medicine 2023;6(1) View
  9. Susanto A, Lyell D, Widyantoro B, Berkovsky S, Magrabi F. Effects of machine learning-based clinical decision support systems on decision-making, care delivery, and patient outcomes: a scoping review. Journal of the American Medical Informatics Association 2023;30(12):2050 View
  10. Huguet N, Chen J, Parikh R, Marino M, Flocke S, Likumahuwa-Ackman S, Bekelman J, DeVoe J. Applying Machine Learning Techniques to Implementation Science. Online Journal of Public Health Informatics 2024;16:e50201 View
  11. Luo Y, Deznabi I, Shaw A, Simsiri N, Rahman T, Fiterau M. Dynamic clustering via branched deep learning enhances personalization of stress prediction from mobile sensor data. Scientific Reports 2024;14(1) View

Books/Policy Documents

  1. Connolly T, Soflano M, Papadopoulos P. Diverse Perspectives and State-of-the-Art Approaches to the Utilization of Data-Driven Clinical Decision Support Systems. View
  2. Negi Y, Marimuthu P, Rauniyar N, Patil U, Shaheen H. Proceedings of Fifth International Conference on Computer and Communication Technologies. View