Standout Papers

Federated semi-supervised learning for COVID region segmentation in chest CT using multi-national data from China... 2021 2026 2022 2024150
  1. Federated semi-supervised learning for COVID region segmentation in chest CT using multi-national data from China, Italy, Japan (2021)
    Dong Yang, Ziyue Xu et al. Medical Image Analysis

Immediate Impact

62 standout
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Citing Papers

Multi-hop graph pooling adversarial network for cross-domain remaining useful life prediction: A distributed federated learning perspective
2024 Standout
Three-year outcomes of post-acute sequelae of COVID-19
2024 Standout
2 intermediate papers

Works of Peng An being referenced

Predicting model of mild and severe types of COVID-19 patients using Thymus CT radiomics model: A preliminary study
2023
Federated semi-supervised learning for COVID region segmentation in chest CT using multi-national data from China, Italy, Japan
2021 Standout

Author Peers

Author Last Decade Papers Cites
Peng An 146 41 44 116 58 43 337
Ali Sabri 239 94 69 68 80 14 341
Victor Savevski 183 68 80 60 82 30 346
Jichan Shi 166 16 30 93 184 21 406
Toktam Khatibi 66 33 42 114 11 36 403
Lionel Tim‐Ee Cheng 155 54 64 61 96 31 407
Koichiro Kimura 177 123 29 72 30 54 363
Abdulaziz A. Qurashi 161 21 14 27 68 30 314
Hui Chen 165 51 25 52 77 35 320
Youn I Choi 50 65 64 33 27 32 304
Serena Carriero 161 84 55 39 57 48 342

All Works

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2026