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Journal of the Endocrine Society|January 29, 2026
Interpretable Machine Learning Model for Survival Prediction in Pediatric Adrenocortical TumorsAntje Redlich, Elisabeth Pfaehler, Marina Kunstreich, et al.
Scientific Reports|May 20, 2025
Value of PET radiomic features for diagnosis and reccurence prediction of newly diagnosed oral squamous cell carcinomaElisabeth Pfaehler, Andreas Schindele, Alexander Dierks, et al.
European Journal of Radiology|March 17, 2025
Interpretable machine learning for thyroid cancer recurrence predicton: Leveraging XGBoost and SHAP analysisAndreas Schindele, Anne Krebold, Ursula Heiß, et al.
European Journal of Nuclear Medicine and Molecular Imaging|August 2, 2020
Machine learning-based analysis of [<sup>18</sup>F]DCFPyL PET radiomics for risk stratification in primary prostate cancerMatthijs C F Cysouw, Bernard H E Jansen, Tim van de Brug, et al.
EJNMMI Physics|March 3, 2022
Noise sensitivity of <sup>89</sup>Zr-Immuno-PET radiomics based on count-reduced clinical imagesAnanthi Somasundaram, David Vállez García, Elisabeth Pfaehler, et al.
European Journal of Nuclear Medicine and Molecular Imaging|June 18, 2025
An exploratory assessment of early and delta PET radiomic features for outcome prediction in locally advanced cervical cancerAnita Florit, Wyanne A Noortman, Nicolò Bizzarri, et al.
Journal of Nuclear Medicine : Official Publication, Society of Nuclear Medicine|March 28, 2024
Is PET Radiomics Useful to Predict Pathologic Tumor Response and Prognosis in Locally Advanced Cervical Cancer?Angela Collarino, Vanessa Feudo, Tina Pasciuto, et al.
EJNMMI Research|September 7, 2020
Predictive value of quantitative <sup>18</sup>F-FDG-PET radiomics analysis in patients with head and neck squamous cell carcinomaRoland M Martens, Thomas Koopman, Daniel P Noij, et al.
Insights Into Imaging|January 16, 2024
METhodological RadiomICs Score (METRICS): a quality scoring tool for radiomics research endorsed by EuSoMIIBurak Kocak, Tugba Akinci D'Antonoli, Nathaniel Mercaldo, et al.
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