2024
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May 16, 2024: Celebrating 40 journal peer-reviews 🥳 See Web of Science for more!


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March 14, 2024: My journal papers 1, 2, 3, 4, and 5 on diagnostic deep learning using chest radiographs are published!



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Feb 21, 2024: My paper on streamlining clinical studies with LLMs is now published by Nature Communications!

    By: S. Tayebi Arasteh, et al. in Nature Communications

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Feb 8, 2024: Celebrating 200 citations on Google Scholar🥳

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Feb 1, 2024: I will be presenting the following 2 abstracts on May 10, 2024 at 105. Deutschen Röntgen­kongress (105th German X-ray congress) in Wiesbaden, Germany!

  • "Tapping the Pool of Non-Medical Images for Enhanced AI-Based Chest Radiography Analysis"

  • "The Future is Collaborative: A Systematic Analysis of Federated Learning and Framework Parameters in the AI-Based Interpretation of Chest Radiographs"

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Jan 17, 2024: Editorial comment on my Radiology AI article by RSNA is available online [Click here]

    "Securing Collaborative Medical AI by Using Differential Privacy: Domain Transfer for Classification of Chest Radiographs"

    By: S. Tayebi Arasteh, et al. in Radiology: Artificial Intelligence (IF: 9.8)

2023
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Dec 16, 2023: Final version of the open-source article is now published! [Click here]

    "Encrypted federated learning for secure decentralized collaboration in cancer image analysis"

    By: D. Truhn*, S. Tayebi Arasteh*, et al. in Medical Image Analysis (IF: 10.9)

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Jul 16, 2023: Our publications 1 and 2 on applying DDPMs on medical images are available in Scientific Reports!

    Kudos to my colleagues Firas Khader and Gustav Müller-Franzes!

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March 21, 2023: Editorial comment on our Radiology article by RSNA is available online [Click here]

    "Using Machine Learning to Reduce the Need for Contrast Agents in Breast MRI through Synthetic Images"

    By: G. Müller-Franzes, L. Huck, S. Tayebi Arasteh, et al. in Radiology (IF: 19.7)

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Feb 1, 2023: I will be presenting the following 2 abstracts on May 13, 2023 in RÖKO 2023!

  • "Automatic Evaluation of Chest Radiographs – The Data Source Matters, But How Much Exactly?" [Click here]
  • "Training of AI Models Beyond the Local Dataset Using Federated Learning with 695,000 Non-Identically-Labeled Chest Radiographs" [Click here]

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Feb 1, 2023: Celebrating 20 citations on Google Scholar🥳

2022
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Nov 29, 2022: RSNA Annual Meeting 2022 in Chicago was amazing!

    I had the opportunity to present my abstract on:
    "Secure Federated Learning for Decentralized Collaboration in Development of AI Models"

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