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

7 from Science/Nature 70 standout
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Works of Cathal McCague 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
Cathal McCague 416 240 196 10 654
Chui-Mei Tiu 315 263 46 18 762
Christopher A. Lovejoy 273 210 299 12 752
Hidenori Machino 234 153 120 25 624
Ge-Ge Wu 441 293 94 10 639
Cheng Jin 539 190 113 32 825
R. Vanguri 298 200 56 20 730
Morteza Heidari 440 325 56 17 582
Jie Wu 457 275 312 16 824
Apeksha Koul 173 249 130 13 678
Niels Olson 339 426 129 8 668

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2026