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Published on in Vol 4 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/62985, first published .
Doctor using stethoscope with medical icons and data visualization

Limitations of Binary Classification for Long-Horizon Diagnosis Prediction and Advantages of a Discrete-Time Time-to-Event Approach: Empirical Analysis

Limitations of Binary Classification for Long-Horizon Diagnosis Prediction and Advantages of a Discrete-Time Time-to-Event Approach: Empirical Analysis

Journals

  1. Su C, Hasebe M. Machine Learning Models for Predicting Acute and Chronic Kidney Diseases During the Post‐Covid‐19 Pandemic. Nephrology 2025;30(7) View
  2. Hill E, Loh D, Davis N, Goldstein B, Dawson G, Engelhard M. Early attention deficit hyperactivity disorder prediction from longitudinal electronic health records. Nature Mental Health 2026;4(5):806 View
  3. Ogliari F, Ferrara M, Huijs J, Traverso A, Barbieri S, Tiano D, Scuri P, Celada D, Papotto L, Mollica L, Oresti S, Ferrara R, Steens M, Steendam C, Merlini A, Luciani A, Lang D, Grisanti S, Genova C, Gemelli M, Flospergher M, Finocchiaro G, El-Soud M, Cortinovis D, Cerea G, Caspani F, Brouns A, Bensch F, Belluomini L, Bareggi C, Albuquerque J, Esposito A, Tacchetti C, Bulotta A, Hendriks L, Reni M. AI-HOPE lung cancer: a multicenter real-world registry integrating artificial intelligence for metastatic non-small-cell lung cancer. ESMO Real World Data and Digital Oncology 2026;13:100736 View