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"Reliability of Machine Learning in Eliminating Data Redundancy of ..."

Yauhen Statsenko et al. (2022)

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DOI: 10.1109/ACCESS.2022.3211080

access: open

type: Journal Article

metadata version: 2022-12-05

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  - https://dblp.org/rec/journals/access/StatsenkoHTKSSS22
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)

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