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Foundations of AI (56)

Published on in Vol 1, No 1 (2022): Jan-Dec

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/41030, first published .
Chronic Disease Prediction Using the Common Data Model: Development Study

Chronic Disease Prediction Using the Common Data Model: Development Study

Chronic Disease Prediction Using the Common Data Model: Development Study

Authors of this article:

Chanjung Lee1 Author Orcid Image ;   Brian Jo1 Author Orcid Image ;   Hyunki Woo1 Author Orcid Image ;   Yoori Im1 Author Orcid Image ;   Rae Woong Park2 Author Orcid Image ;   ChulHyoung Park2 Author Orcid Image
Article Authors Cited by (13) Tweetations (1) Metrics

Journals

  1. Biró A, Cuesta-Vargas A, Szilágyi L. Precognition of mental health and neurogenerative disorders using AI-parsed text and sentiment analysis. Acta Universitatis Sapientiae, Informatica 2023;15(2):359 View
  2. El Emam K, Leung T, Malin B, Klement W, Eysenbach G. Consolidated Reporting Guidelines for Prognostic and Diagnostic Machine Learning Models (CREMLS). Journal of Medical Internet Research 2024;26:e52508 View
  3. Khosravi H, Ahmed I, Choudhury A. Predicting Suicidal Ideation, Planning, and Attempts among the Adolescent Population of the United States. Healthcare 2024;12(13):1262 View
  4. Meng J, Niu X, Luo C, Chen Y, Li Q, Wei D. Development and Validation of a Machine Learning–Based Early Warning Model for Lichenoid Vulvar Disease: Prediction Model Development Study. Journal of Medical Internet Research 2024;26:e55734 View
  5. Shahsavar Y, Choudhury A, Onu J. Behavioral and social predictors of suicidal ideation and attempts among adolescents and young adults. PLOS Mental Health 2025;2(1):e0000221 View
  6. Makarov N, Lipkovich M. A transformer-based model for next disease prediction using electronic health records. The European Physical Journal Special Topics 2025 View
  7. Xie H. A capsule network-based public health prediction system for chronic diseases: clinical and community implications. Frontiers in Public Health 2025;13 View
  8. Lee J, Lee H, Lee H, Park T, Jin K, Kim D, Ryu B. Comparing large scale and selected feature learning for community acquired pneumonia prognosis prediction using clinical data: a stacked ensemble approach. Scientific Reports 2025;15(1) View
  9. Adams A, Lee C, Escobar G, Bayliss E, Callaghan B, Horberg M, Schmittdiel J, Trinacty C, Gilliam L, Kim E, Hejazi N, Ma L, Neugebauer R. Estimating the Risk of Lower Extremity Complications in Adults Newly Diagnosed With Diabetic Polyneuropathy: Retrospective Cohort Study. JMIR Diabetes 2025;10:e60141 View
  10. Jin T, Halili A. Predicting the risk of depression in older adults with disability using machine learning: an analysis based on CHARLS data. Frontiers in Artificial Intelligence 2025;8 View
  11. Fahmy A. Exploring the Role of AI in Predicting Chronic Disease Progression: Diabetes and Cardiovascular Diseases. Premier Journal of Public Health 2025 View

Books/Policy Documents

  1. Rajeev C, Natarajan K. Revolutionizing Healthcare 5.0: The Power of Generative AI. View

Conference Proceedings

  1. Poongodi S, Sasirekha K, Rini S, S J, Rashmi G. 2025 International Conference on Inventive Computation Technologies (ICICT). An Enchanced Approach for Early Chronic Kidney Disease Prediction Using Advanced Machine Learning and Data Processing Techniques View