Published on in Vol 26 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/55986, first published .
Accuracy of Machine Learning in Detecting Pediatric Epileptic Seizures: Systematic Review and Meta-Analysis

Accuracy of Machine Learning in Detecting Pediatric Epileptic Seizures: Systematic Review and Meta-Analysis

Accuracy of Machine Learning in Detecting Pediatric Epileptic Seizures: Systematic Review and Meta-Analysis

Journals

  1. Bai L, Litscher G, Li X. Epileptic Seizure Detection Using Machine Learning: A Systematic Review and Meta-Analysis. Brain Sciences 2025;15(6):634 View
  2. Nariai H. Frontiers in EEG as a tool for the management of pediatric epilepsy: Past, present, and future. Epilepsia Open 2025 View
  3. Bangash A, Bercu M, Byrne R, Pavuluri S, Salehi A. Application of machine learning approaches to predict seizure-onset zones in patients with drug-resistant epilepsy: a systematic review. Frontiers in Neurology 2025;16 View
  4. Mohamed S, Ben-Jaafar A, Frimpong M, Roy S, Sanker V, Nkrumah-Boateng P, Imran S, Mumeen A, Mohamed S, Wireko A. Applying artificial intelligence in neurodevelopmental disorders management and research. European Journal of Medical Research 2026;31(1) View
  5. Zhang X, Liu C, Sun Y, You L, Zhang X, Shang H. Clinical research on artificial intelligence medical diagnostic devices: A scoping review. EngMedicine 2026;3(1):100120 View
  6. Mondillo G, Perrotta A, Masino M, Colosimo S, Frattolillo V, Abbate F. Artificial Intelligence and Precision Pharmacotherapy in Pediatrics: A New Paradigm in Therapeutic Decision-Making. Therapeutics 2026;3(1):6 View
  7. Zhong Y, Xu C, Gao Y, Ma H, Liu Y, Yan W, Ma Y, Liu X, Li X. Differentiating bipolar disorder and schizophrenia using sleep EEG power and coherence features: A machine learning approach based on polysomnography. Journal of Affective Disorders 2026;403:121478 View