Standout Papers

End-to-end privacy preserving deep learning on multi-institutional medical imaging 2021 2026 2022 2024221
  1. End-to-end privacy preserving deep learning on multi-institutional medical imaging (2021)
    Georgios Kaissis, Alexander Ziller et al. Nature Machine Intelligence
  2. Evaluation and mitigation of the limitations of large language models in clinical decision-making (2024)
    Paul Hager, Friederike Jungmann et al. Nature Medicine

Immediate Impact

58 standout
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Citing Papers

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1 intermediate paper

Works of Friederike Jungmann being referenced

End-to-end privacy preserving deep learning on multi-institutional medical imaging
2021 Standout

Author Peers

Author Last Decade Papers Cites
Friederike Jungmann 212 92 282 152 15 528
Subrato Bharati 225 26 291 81 32 614
Ruchi Singla 184 32 194 140 10 601
Shaoping Hu 250 75 160 59 19 577
Matthew B. A. McDermott 203 38 243 280 12 583
Xiaoming Qiu 455 36 203 124 18 573
Jesutofunmi A. Omiye 108 52 159 190 16 485
Kazuma Kobayashi 215 35 163 75 31 537
Sertan Serte 417 85 317 50 18 629
Vajira Thambawita 131 43 183 76 19 582
Fnu Amisha 177 36 130 235 20 577

All Works

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2026