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2. Federated Learning Enables Big Data for Rare Cancer Boundary Detection

3. The use of machine learning/deep learning in PET/CT interpretation to aid in outcome prediction in lymphoma

4. Temporal evolution of chest radiographic appearances in COVID-19 with clinicoradiological associations: a multicentre United Kingdom resident-led study

5. Author Correction: Federated learning enables big data for rare cancer boundary detection

14. Prediction of Patient Outcomes in Locally Advanced Cervical Carcinoma Following Chemoradiotherapy—Comparative Effectiveness of Magnetic Resonance Imaging and 2-Deoxy-2-[ 18 F]fluoro-D-glucose Imaging.

15. Comparative effectiveness of standard vs. AI-assisted PET/CT reading workflow for pre-treatment lymphoma staging: a multi-institutional reader study evaluation.

16. Imaging Spectrum of the Developing Glioblastoma: A Cross-Sectional Observation Study

18. An Automated Method for Artifical Intelligence Assisted Diagnosis of Active Aortitis Using Radiomic Analysis of FDG PET-CT Images

20. Prediction of patient outcome in locally advanced cervical carcinoma following chemoradiotherapy - comparative effectiveness of MRI and FDG PET-CT

21. Reporter confidence of an AI-assisted PET/CT reading workflow in pre-treatment assessment of high-grade lymphoma : multi-centre reader study

22. Federated learning enables big data for rare cancer boundary detection

25. Exploratory Analysis of Serial 18F-fluciclovine PET-CT and Multiparametric MRI during Chemoradiation for Glioblastoma

30. Exploratory Analysis of Serial 18 F-fluciclovine PET-CT and Multiparametric MRI during Chemoradiation for Glioblastoma.

32. Vascular interventions for renal transplants

36. The use of treadmill training to recover locomotor ability in patients with spinal cord injury.

37. 18F-FDG PET-CT in paediatric oncology: established and emerging applications.

38. An Automated Method for Artifical Intelligence Assisted Diagnosis of Active Aortitis Using Radiomic Analysis of FDG PET-CT Images.

39. 18 F-FDG PET-CT in paediatric oncology: established and emerging applications.

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