This paper is in the following e-collection/theme issue:

Applications of AI (289) Ethical, Legal, and Social Issues in AI (105) Lung Cancer (66) Ethics, Privacy, and Legal Issues (621) Artificial Intelligence (2144) eHealth Infrastructures (430)

Published on in Vol 4 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/60847, first published .
Advancing Privacy-Preserving Health Care Analytics and Implementation of the Personal Health Train: Federated Deep Learning Study

Advancing Privacy-Preserving Health Care Analytics and Implementation of the Personal Health Train: Federated Deep Learning Study

Advancing Privacy-Preserving Health Care Analytics and Implementation of the Personal Health Train: Federated Deep Learning Study

Authors of this article:

Ananya Choudhury1, 2 Author Orcid Image ;   Leroy Volmer1, 2 Author Orcid Image ;   Frank Martin3 Author Orcid Image ;   Rianne Fijten1, 2 Author Orcid Image ;   Leonard Wee1, 2 Author Orcid Image ;   Andre Dekker1, 2, 4 Author Orcid Image ;   Johan van Soest1, 2, 4 Author Orcid Image
Article Authors Cited by (12) Tweetations Metrics

Journals

  1. Shah K, Paganetti H, Yepes P, Hong T, Wo J, Roberts J, Koay E, Guthier C, Chamseddine I. Linear Federated Learning for Outcome Prediction With Application to Hepatocellular Carcinoma Radiotherapy. JCO Clinical Cancer Informatics 2025;(9) View
  2. Hope A, Mundis M, Sonke J, Kang J, Korreman S, Napolitano B, Elguindi S, Joiner M, Burmeister J, Dominello M. Three discipline collaborative radiation therapy (3DCRT) special debate: AI structure segmentation is better than clinician contouring for both OARs and targets. Journal of Applied Clinical Medical Physics 2025;26(7) View
  3. Fahmy A. Assessing the Efficacy of AI Models in Medical Imaging Analysis for the Early Identification of Diabetic Foot Ulcers and Gangrene: A Review. Premier Journal of Science 2025 View
  4. Liu H, Ma C, Jiang T, Li Y, Chen R, Tian Y. Establishing a High-quality Biomedical Resource for Rare Diseases：<?A3B2 pi6?>Insights from Pediatric Medulloblastoma. Bulletin of National Natural Science Foundation of China 2025;39(4):635 View
  5. Tong J, Chen D, Li J, Chen H, Yu T. Radiotherapy for primary bone tumors: current techniques and integration of artificial intelligence—a review. Frontiers in Oncology 2025;15 View
  6. Goodings A, Fadahunsi K, Tarn D, Lutomski J, Chhor A, Shiely F, Henn P, O'Donoghue J. Determinants of Continuous Smartwatch Use and Data-Sharing Preferences With Physicians, Public Health Authorities, and Private Companies: Cross-Sectional Survey of Smartwatch Users. Journal of Medical Internet Research 2025;27:e67414 View
  7. Tanveer F, Iradat F, Iqbal W, Alsagri H, Alhakbani H, Ahmad A, Khan F. Balancing privacy and performance in healthcare: A federated learning framework for sensitive data. DIGITAL HEALTH 2025;11 View
  8. Shah S, Ali Z, Waqar M, Kim A. Federated Learning in Public Health: A Systematic Review of Decentralized, Equitable, and Secure Disease Prevention Approaches. Healthcare 2025;13(21):2760 View
  9. Henna F, Kashaf Batool S, Siddiqui H, Riaz A, Javed A, Kamran A, Faisal F, Shadab H, Qamar A, Mehboob J, Rahman R, Furqan H, Luqman M, Bacha Z. Narrative Review on Explainable Artificial Intelligence for Multimodal Risk Stratification in Coronary Artery Disease. Cardiology in Review 2025 View
  10. Lu Y, Chen C, Qiu J, Ji Q, Zhou L, Xiong H, Wu T. Systematic review and comparison of machine learning and conventional statistical models for predicting cardiovascular events in dialysis patients. Renal Failure 2025;47(1) View

Books/Policy Documents

  1. Kaur G, Wasson V, Kaur S. Blockchain and Federated Learning Synergy for Privacy-Focused DeepFex Solutions. View
  2. Dafik , Aarthi N, Kumar B, Sebastian A, Bathrinath S, Wankhede D. Machine Learning in Healthcare. View