


default search action
"Reliability of Machine Learning in Eliminating Data Redundancy of ..."
Yauhen Statsenko et al. (2022)
- Yauhen Statsenko
, Tetiana Habuza
, Tatsiana Talako
, Tetiana Kurbatova
, Gillian Lylian Simiyu
, Darya Smetanina
, Juana Sido
, Dana Sharif Qandil
, Sarah Meribout
, Juri G. Gelovani
, Klaus Neidl-Van Gorkom
, Taleb M. Almansoori
, Fatmah Al Zahmi
, Tom Loney
, Anthony Bedson
, Nerissa Naidoo
, Alireza Dehdashtian
, Milos Ljubisavljevic
, Jamal Al Koteesh
, Karuna M. Das
:
Reliability of Machine Learning in Eliminating Data Redundancy of Radiomics and Reflecting Pathophysiology in COVID-19 Pneumonia: Impact of CT Reconstruction Kernels on Accuracy. IEEE Access 10: 120901-120921 (2022)

manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.