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Radiology. Artificial Intelligence|January 2, 2024
Deep Learning-based Identification of Brain MRI Sequences Using a Model Trained on Large Multicentric Study CohortsMustafa Ahmed Mahmutoglu, Chandrakanth Jayachandran Preetha, Hagen Meredig, et al.Neuro-Oncology Practice|July 20, 2022
Corticosteroids use and neurocognitive functioning in patients with recurrent glioblastoma: Evidence from European Organization for Research and Treatment of Cancer (EORTC) trial 26101Ivan Caramanna, Julie M de Kort, Alba A Brandes, et al.Radiology. Artificial Intelligence|October 16, 2024
Addressing the Generalizability of AI in Radiology Using a Novel Data Augmentation Framework with Synthetic Patient Image Data: Proof-of-Concept and External Validation for Classification Tasks in Multiple SclerosisGianluca Brugnara, Chandrakanth Jayachandran Preetha, Katerina Deike, et al.The Lancet. Digital Health|October 24, 2021
Deep-learning-based synthesis of post-contrast T1-weighted MRI for tumour response assessment in neuro-oncology: a multicentre, retrospective cohort studyChandrakanth Jayachandran Preetha, Hagen Meredig, Gianluca Brugnara, et al.Medical Image Analysis|November 9, 2020
A global benchmark of algorithms for segmenting the left atrium from late gadolinium-enhanced cardiac magnetic resonance imagingZhaohan Xiong, Qing Xia, Zhiqiang Hu, et al.Pageof 1