Standout Papers

Common pitfalls and recommendations for using machine learning to detect and prognosticate for COVID-19 using... 2020 2026 2022 2024513
  1. Common pitfalls and recommendations for using machine learning to detect and prognosticate for COVID-19 using chest radiographs and CT scans (2020)
    Michael Roberts, Derek Driggs et al. Research Explorer (The University of Manchester)

Immediate Impact

1 by Nobel laureates 7 from Science/Nature 70 standout
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5 intermediate papers

Works of Christian Etmann being referenced

Common pitfalls and recommendations for using machine learning to detect and prognosticate for COVID-19 using chest radiographs and CT scans
2020 Standout

Author Peers

Author Last Decade Papers Cites
Christian Etmann 339 190 89 240 6 622
Julian Gilbey 366 188 105 223 10 726
Niels Olson 339 129 71 426 8 668
Coryandar Gilvary 184 97 251 163 5 671
Ole-Johan Skrede 365 73 64 281 4 589
Ruchi Singla 184 140 44 194 10 601
Arvind Rao 218 27 104 54 18 551
Jannis Born 212 66 296 113 24 667
Kevin Wu 101 165 180 95 9 521
Derek Driggs 325 188 44 227 7 562
Alice Yu 496 95 31 67 20 689

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2026