Published on in Vol 25 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/46165, first published .
Privacy-Preserving Federated Model Predicting Bipolar Transition in Patients With Depression: Prediction Model Development Study

Privacy-Preserving Federated Model Predicting Bipolar Transition in Patients With Depression: Prediction Model Development Study

Privacy-Preserving Federated Model Predicting Bipolar Transition in Patients With Depression: Prediction Model Development Study

Journals

  1. Kim Y, Koo J, Lee S, Song H, Lee M. Explainable Artificial Intelligence Warning Model Using an Ensemble Approach for In-Hospital Cardiac Arrest Prediction: Retrospective Cohort Study. Journal of Medical Internet Research 2023;25:e48244 View
  2. Khalil S, Tawfik N, Spruit M. Exploring the potential of federated learning in mental health research: a systematic literature review. Applied Intelligence 2024;54(2):1619 View
  3. Kim C, Yu D, Baek H, Cho J, You S, Park R. Data Resource Profile: Health Insurance Review and Assessment Service Covid-19 Observational Medical Outcomes Partnership (HIRA Covid-19 OMOP) database in South Korea. International Journal of Epidemiology 2024;53(3) View