Published on in Vol 21, No 3 (2019): March

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/11990, first published .
Detecting Hypoglycemia Incidents Reported in Patients’ Secure Messages: Using Cost-Sensitive Learning and Oversampling to Reduce Data Imbalance

Detecting Hypoglycemia Incidents Reported in Patients’ Secure Messages: Using Cost-Sensitive Learning and Oversampling to Reduce Data Imbalance

Detecting Hypoglycemia Incidents Reported in Patients’ Secure Messages: Using Cost-Sensitive Learning and Oversampling to Reduce Data Imbalance

Journals

  1. Ferrario A, Demiray B, Yordanova K, Luo M, Martin M. Social Reminiscence in Older Adults’ Everyday Conversations: Automated Detection Using Natural Language Processing and Machine Learning. Journal of Medical Internet Research 2020;22(9):e19133 View
  2. López Seguí F, Ander Egg Aguilar R, de Maeztu G, García-Altés A, García Cuyàs F, Walsh S, Sagarra Castro M, Vidal-Alaball J. Teleconsultations between Patients and Healthcare Professionals in Primary Care in Catalonia: The Evaluation of Text Classification Algorithms Using Supervised Machine Learning. International Journal of Environmental Research and Public Health 2020;17(3):1093 View
  3. Hung L, Sung S, Hu Y. A Machine Learning Approach to Predicting Readmission or Mortality in Patients Hospitalized for Stroke or Transient Ischemic Attack. Applied Sciences 2020;10(18):6337 View
  4. Mujahid O, Contreras I, Vehi J. Machine Learning Techniques for Hypoglycemia Prediction: Trends and Challenges. Sensors 2021;21(2):546 View
  5. Kodama S, Fujihara K, Shiozaki H, Horikawa C, Yamada M, Sato T, Yaguchi Y, Yamamoto M, Kitazawa M, Iwanaga M, Matsubayashi Y, Sone H. Ability of Current Machine Learning Algorithms to Predict and Detect Hypoglycemia in Patients With Diabetes Mellitus: Meta-analysis. JMIR Diabetes 2021;6(1):e22458 View
  6. Pilla S, Park J, Schwartz J, Albert M, Ephraim P, Boulware L, Mathioudakis N, Maruthur N, Beach M, Greer R. Hypoglycemia Communication in Primary Care Visits for Patients with Diabetes. Journal of General Internal Medicine 2021;36(6):1533 View
  7. JENIE R, NURDIN N, HUSEIN I, ALATAS H. Sensitivity and Specificity of Non-Invasive Blood Glucose Level Measurement Optical Device to Detect Hypoglycaemia. Journal of Nutritional Science and Vitaminology 2020;66(Supplement):S226 View
  8. Turchin A, Florez Builes L. Using Natural Language Processing to Measure and Improve Quality of Diabetes Care: A Systematic Review. Journal of Diabetes Science and Technology 2021;15(3):553 View
  9. Sung S, Hung L, Hu Y. Developing a stroke alert trigger for clinical decision support at emergency triage using machine learning. International Journal of Medical Informatics 2021;152:104505 View