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Showing 1–7 of 7 results
Advanced filters: Author: Daguang Xu Clear advanced filters
  • Federated learning, a method for training artificial intelligence algorithms that protects data privacy, was used to predict future oxygen requirements of symptomatic patients with COVID-19 using data from 20 different institutes across the globe.

    • Ittai Dayan
    • Holger R. Roth
    • Quanzheng Li
    Research
    Nature Medicine
    Volume: 27, P: 1735-1743
  • Chest CT is emerging as a valuable diagnostic tool for clinical management of COVID-19 associated lung disease. Here, the authors present a multinational study on the application of deep learning algorithms for COVID-19 diagnosis against multiple lung conditions as controls.

    • Stephanie A. Harmon
    • Thomas H. Sanford
    • Baris Turkbey
    ResearchOpen Access
    Nature Communications
    Volume: 11, P: 1-7
  • International challenges have become the de facto standard for comparative assessment of image analysis algorithms. Here, the authors present the results of a biomedical image segmentation challenge, showing that a method capable of performing well on multiple tasks will generalize well to a previously unseen task.

    • Michela Antonelli
    • Annika Reinke
    • M. Jorge Cardoso
    ResearchOpen Access
    Nature Communications
    Volume: 13, P: 1-13
  • Federated learning can be used to train medical AI models on sensitive personal data while preserving important privacy properties; however, the sensitive nature of the data makes it difficult to evaluate approaches reproducibly on real data. The MedPerf project presented by Karargyris et al. provides the tools and infrastructure to distribute models to healthcare facilities, such that they can be trained and evaluated in realistic settings.

    • Alexandros Karargyris
    • Renato Umeton
    • Peter Mattson
    ResearchOpen Access
    Nature Machine Intelligence
    Volume: 5, P: 799-810