Published on in Vol 24 , No 7 (2022) :July

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/37233, first published .
Drug Recommendation System for Diabetes Using a Collaborative Filtering and Clustering Approach: Development and Performance Evaluation

Drug Recommendation System for Diabetes Using a Collaborative Filtering and Clustering Approach: Development and Performance Evaluation

Drug Recommendation System for Diabetes Using a Collaborative Filtering and Clustering Approach: Development and Performance Evaluation

Journals

  1. Tan W, Gao Q, Oei R, Hsu W, Lee M, Tan N. Diabetes medication recommendation system using patient similarity analytics. Scientific Reports 2022;12(1) View
  2. Sae-Ang A, Chairat S, Tansuebchueasai N, Fumaneeshoat O, Ingviya T, Chaichulee S. Drug Recommendation from Diagnosis Codes: Classification vs. Collaborative Filtering Approaches. International Journal of Environmental Research and Public Health 2022;20(1):309 View
  3. Howell P, Aryal A, Wu C. Web-Based Patient Recommender Systems for Preventive Care: Protocol for Empirical Research Propositions. JMIR Research Protocols 2023;12:e43316 View
  4. 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
  5. Zhang Y, Zhang D, Liu X, Peng W, Mu Y, Li Y, Qiu Q. A Practical Statin Recommendation System Based on Real-World Data to Improve LDL-C Management in Secondary Prevention. Journal of Cardiovascular Pharmacology 2023;81(5):373 View