Semi-supervised learning for an improved diagnosis of COVID-19 in CT images

Open Access

Peer-reviewed

Research Article

About the Authors

Chang Hee Han

Roles Data curation, Formal analysis, Investigation, Methodology, Validation, Visualization, Writing – original draft, Writing – review & editing

Affiliation Department of Computer Science and Engineering, Sejong University, Seoul, Korea

Misuk Kim

Roles Methodology, Validation, Visualization, Writing – review & editing

Affiliation Department of Data Science, Sejong University, Seoul, Korea

Jin Tae Kwak

Roles Conceptualization, Methodology, Project administration, Supervision, Validation, Visualization, Writing – review & editing

Affiliation School of Electrical Engineering, Korea University, Seoul, Korea

The authors have declared that no competing interests exist

COVID 19
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Computed axial tomography
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Virus testing
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Pulmonary imaging
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Convolution
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Deep learning
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Pneumonia
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Lung and intrathoracic tumors
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