Published on in Vol 10, No 12 (2022): December

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/37833, first published .
Implementation of Machine Learning Pipelines for Clinical Practice: Development and Validation Study

Implementation of Machine Learning Pipelines for Clinical Practice: Development and Validation Study

Implementation of Machine Learning Pipelines for Clinical Practice: Development and Validation Study

Journals

  1. Zoodsma R, Bosch R, Alderliesten T, Bollen C, Kappen T, Koomen E, Siebes A, Nijman J. Continuous Data-Driven Monitoring in Critical Congenital Heart Disease: Clinical Deterioration Model Development. JMIR Cardio 2023;7:e45190 View
  2. Wissel B, Greiner H, Glauser T, Mangano F, Holland‐Bouley K, Zhang N, Szczesniak R, Santel D, Pestian J, Dexheimer J. Automated, machine learning–based alerts increase epilepsy surgery referrals: A randomized controlled trial. Epilepsia 2023;64(7):1791 View
  3. Woodman R, Mangoni A. A comprehensive review of machine learning algorithms and their application in geriatric medicine: present and future. Aging Clinical and Experimental Research 2023;35(11):2363 View
  4. Kerr W, McFarlane K. Machine Learning and Artificial Intelligence Applications to Epilepsy: a Review for the Practicing Epileptologist. Current Neurology and Neuroscience Reports 2023;23(12):869 View
  5. Rabindranath M, Naghibzadeh M, Zhao X, Holdsworth S, Brudno M, Sidhu A, Bhat M. Clinical Deployment of Machine Learning Tools in Transplant Medicine: What Does the Future Hold?. Transplantation 2023 View
  6. Završnik J, Kokol P, Žlahtič B, Blažun Vošner H. Artificial Intelligence and Pediatrics: Synthetic Knowledge Synthesis. Electronics 2024;13(3):512 View
  7. Foote H, Cohen-Wolkowiez M, Lindsell C, Hornik C. Applying Artificial Intelligence in Pediatric Clinical Trials: Potential Impacts and Obstacles. The Journal of Pediatric Pharmacology and Therapeutics 2024;29(3):336 View