Artificial Intelligence in Healthcare

AI, Machine Learning, and Deep and Intelligent Medicine Simplified for Everyone

Academic Edition, Chapter 7 - References/Further Reading

General Edition, Chapter 6 - References/Further Reading

 

  1. Johnson K. How federated learning could shape the future of AI in a privacy-obsessed world [Internet]. VentureBeat. 2019 [cited 2021 Apr 5]. Available from: https://venturebeat.com/2019/06/03/how-federated-learning-could-shape-the-future-of-ai-in-a-privacy-obsessed-world/
  2. McMahan HB, Moore E, Ramage D, Hampson S, Arcas BA y. Communication-efficient learning of deep networks from decentralized data [Internet]. arXiv [cs.LG]. 2016. Available from: http://arxiv.org/abs/1602.05629
  3. Rieke N, Hancox J, Li W, Milletarì F, Roth HR, Albarqouni S, et al. The future of digital health with federated learning. NPJ Digit Med. 2020;3(1):119.
  4. Li W, Milletarì F, Xu D, Rieke N, Hancox J, Zhu W, et al. Privacy-preserving federated brain tumour segmentation. In: Machine Learning in Medical Imaging. Cham: Springer International Publishing; 2019. p. 133–41.
  5. Sheller MJ, Reina GA, Edwards B, Martin J, Bakas S. Multi-institutional deep learning modeling without sharing patient data: A feasibility study on brain tumor segmentation. Brainlesion. 2019;11383:92–104.
  6. Rocher L, Hendrickx JM, de Montjoye Y-A. Estimating the success of re-identifications in incomplete datasets using generative models. Nat Commun. 2019;10(1):3069.
  7. Kumar TS, Vijai A. 3D reconstruction of face from 2D CT scan images. Procedia Eng. 2012;30:970–7.
  8. Schwarz CG, Kremers WK, Therneau TM, Sharp RR, Gunter JL, Vemuri P, et al. Identification of anonymous MRI research participants with face-recognition software. N Engl J Med. 2019;381(17):1684–6.
  9. Kim A. How federated learning can help healthcare CIOs [Internet]. Publisher. 2020 [cited 2021 Apr 5]. Available from: https://healthtechmagazine.net/article/2020/08/how-federated-learning-can-help-healthcare-cios
  10. Owkin Connect, our Federated Learning software - OWKIN [Internet]. Owkin.com. 2021 [cited 2021 Apr 5]. Available from: https://owkin.com/owkin-connect/
  11. Powell K. AI privacy enabled with Clara Federated Learning [Internet]. Nvidia.com. 2019 [cited 2021 Apr 5]. Available from: https://blogs.nvidia.com/blog/2019/12/01/clara-federated-learning/
  12. Lee J, Sun J, Wang F, Wang S, Jun C-H, Jiang X. Privacy-preserving patient similarity learning in a federated environment: Development and analysis. JMIR Med Inform. 2018;6(2):e20.
  13. Huang L, Shea AL, Qian H, Masurkar A, Deng H, Liu D. Patient clustering improves efficiency of federated machine learning to predict mortality and hospital stay time using distributed electronic medical records. J Biomed Inform. 2019;99(103291):103291.
  14. Brisimi TS, Chen R, Mela T, Olshevsky A, Paschalidis IC, Shi W. Federated learning of predictive models from federated Electronic Health Records. Int J Med Inform. 2018;112:59–67.
  15. HealthChain project — Substra Foundation [Internet]. Substra.ai. [cited 2021 Apr 5]. Available from: https://www.substra.ai/en/healthchain-project
  16. The Federated Tumor Segmentation (FeTS) initiative [Internet]. Fets.ai. [cited 2021 Apr 5]. Available from: https://www.fets.ai/
  17. Machine learning ledger orchestration for drug discovery [Internet]. Europa.eu. [cited 2021 Apr 5]. Available from: https://cordis.europa.eu/project/id/831472