Standout Papers

How medical AI devices are evaluate... 2012 2026 2016 2021 556
  1. How medical AI devices are evaluated: limitations and recommendations from an analysis of FDA approvals (2021)
    Eric Q. Wu, Kevin Wu et al. Nature Medicine
  2. Large Language Models in Medicine: The Potentials and Pitfalls (2024)
    Jesutofunmi A. Omiye, Haiwen Gui et al. Annals of Internal Medicine
  3. Lack of Transparency and Potential Bias in Artificial Intelligence Data Sets and Algorithms (2021)
    Roxana Daneshjou, Mary Sun et al. JAMA Dermatology
  4. Data-Driven Prediction of Drug Effects and Interactions (2012)
    Nicholas P. Tatonetti, Roxana Daneshjou et al. Science Translational Medicine

Immediate Impact

14 from Science/Nature 57 standout
Sub-graph 1 of 22

Citing Papers

Medical Image Segmentation Review: The Success of U-Net
2024 Standout
Bias in medical AI: Implications for clinical decision-making
2024 Standout

Works of Roxana Daneshjou being referenced

Lack of Transparency and Potential Bias in Artificial Intelligence Data Sets and Algorithms
2021 Standout
How medical AI devices are evaluated: limitations and recommendations from an analysis of FDA approvals
2021 Standout

Author Peers

Author Last Decade Papers Cites
Roxana Daneshjou 597 323 567 547 68 2.2k
Jianying Hu 529 48 288 449 62 1.8k
Christian Reich 575 136 90 543 54 2.8k
Ping Zhang 493 161 73 989 124 2.4k
Kenneth Jung 345 368 277 843 26 2.4k
Qingyu Chen 660 187 200 697 116 2.5k
Jon Duke 396 91 62 433 48 2.0k
Li Zhou 724 113 174 470 162 3.1k
Jeremy L. Warner 472 702 112 676 157 2.5k
David Page 561 150 41 583 78 2.5k
Peggy Peissig 740 103 72 914 86 2.6k

All Works

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Rankless by CCL
2026