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Sergey Primakov

Maastricht University

19

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98

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Precision-medicine-toolbox: An open-source python package for facilitation of quantitative medical imaging and radiomics analysis.

2022 CoRR
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Reply to Orlhac, F.; Buvat, I. Comment on "Ibrahim et al. The Effects of In-Plane Spatial Resolution on CT-Based Radiomic Features' Stability with and without ComBat Harmonization. Cancers 2021, 13, 1848".

2021 Cancers
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A Prospectively Validated Prognostic Model for Patients with Locally Advanced Squamous Cell Carcinoma of the Head and Neck Based on Radiomics of Computed Tomography Images

2021 Cancers
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MRI-Based Radiomics Analysis for the Pretreatment Prediction of Pathologic Complete Tumor Response to Neoadjuvant Systemic Therapy in Breast Cancer Patients: A Multicenter Study

2021 Cancers
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Deep learning for the fully automated segmentation of the inner ear on MRI.

2021 Scientific Reports
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OC-0557 AI-based NSCLC detection and segmentation: faster and more prognostic than manual segmentation

2021 Radiotherapy and Oncology
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Reproducibility of CT-Based Hepatocellular Carcinoma Radiomic Features across Different Contrast Imaging Phases: A Proof of Concept on SORAMIC Trial Data.

2021 Cancers
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Can predicting COVID-19 mortality in a European cohort using only demographic and comorbidity data surpass age-based prediction: An externally validated study.

2021 PLOS ONE
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The application of a workflow integrating the variable reproducibility and harmonizability of radiomic features on a phantom dataset.

2021 PLOS ONE
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The Effects of In-Plane Spatial Resolution on CT-Based Radiomic Features’ Stability with and without ComBat Harmonization

2021 Cancers
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