Improving radiomics-based isocitrate dehydrogenase 1 prediction in glioma patients using semi-supervised machine learning models

Amir Mahmoud Ahmadzadeh; Amirhossein Jafarnezhad; Danial Elyassirad; Mahsa Vatanparast; Benyamin Gheiji; Shahriar Faghani

doi:10.1186/s12880-025-02040-1

Abstract

Semi-supervised approaches may improve the performance of radiomics-based ML models in predicting glioma IDH1 status. Using pseudolabels, these models can increase the size of training data, potentially leading to enhancement of model predictive performance. Additionally, these models may improve prediction efficiency by requiring fewer image sequences.

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Year: 2025
Type: article
Citations: 0
Access: Closed

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APA Style

                            
                                    Amir Mahmoud Ahmadzadeh, 
                                
                                    Amirhossein Jafarnezhad, 
                                
                                    Danial Elyassirad
                                
                                et al.
                            
                            (2025). 
                            Improving radiomics-based isocitrate dehydrogenase 1 prediction in glioma patients using semi-supervised machine learning models. 
                            BMC Medical Imaging
                            
                            .
                            https://doi.org/10.1186/s12880-025-02040-1

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DOI: 10.1186/s12880-025-02040-1