A Machine Learning Model Based on Radiomic Features as a Tool to Identify Active Giant Cell Arteritis on [¹⁸F]FDG-PET Images During Follow-Up by Hanne S. Vries, Gijs D. van Praagh, Pieter H. Nienhuis, Lejla Alic, Riemer H. J. A. Slart

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Radiomics with Clinical Data and [¹⁸F]FDG-PET for Differentiating Between Infected and Non-Infected Intracavitary Vascular (Endo)Grafts: A Proof-of-Concept Study by Gijs D. van Praagh, Francine Vos, Stijn Legtenberg, Marjan Wouthuyzen-Bakker, Ilse J. E. Kouijzer, Erik H. J. G. Aarntzen, Jean-Paul P. M. de Vries, Riemer H. J. A. Slart, Lejla Alic, Bhanu Sinha, Ben R. Saleem

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Whole-body and site specific [18F]FDG uptake patterns on PET/CT have limited value in differentiating between polymyalgia rheumatica and other inflammatory diseases: two cohorts of... by Andreas Wiggers Nielsen, Gijs D. van Praagh, Kornelis S. M. van der Geest, Ib Tønder Hansen, Berit Dalsgaard Nielsen, Søren Geill Kjær, Jesper Blegvad-Nissen, Kate Rewers, Christian Møller Sørensen, Elisabeth Brouwer, Ellen-Margrethe Hauge, Lars Christian Gormsen, Riemer H. J. A. Slart, Kresten Krarup Keller

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