Comprehensive Cancer Center Vienna

The role of artificial intelligence in informed patient consent for radiotherapy treatments—a case report

Matthias Moll, Gerd Heilemann, Dietmar Georg et al.

2024 · 11 Zit.

Augmenting Insufficiently Accruing Oncology Clinical Trials Using Generative Models: Validation Study

Samer El Kababji, Nicholas Mitsakakis, Elizabeth Jonker et al.

2025 · 11 Zit.

AGREE II Quality Assessment of National and International Clinical Practice Guidelines on Prostate Cancer Management by the OPTIMA Consortium

Vasileios Sakalis, Yagnaseni Bhattacharya, Katharina Beyer et al.

2024 · 5 Zit.

Digital support and artificial intelligence in cancer patients undergoing radiation therapy: patient utilization, acceptance and attitudes

Franziska Springer, Peter Hambsch, Anja Mehnert et al.

2025 · 2 Zit.

The Dawn of Quantum AI in Nuclear Medicine: an EANM Perspective

László Papp, Dimitris Visvikis, Martina Sollini et al.

2026 · 0 Zit.

Editorial: Artificial intelligence will shape the future of urology but good things come to those who wait

Benjamin Pradère, Karim Bensalah

2021 · 0 Zit.

Re: Artificial Intelligence Tools Expand Scientists’ Impact but Contract Science’s Focus

David D’Andrea, Riccardo Campi

2026 · 0 Zit.

Harnessing Artificial Intelligence for Risk Stratification and Outcome Prediction in Urologic Cancers: A Systematic Review

Navid Roessler, Marcin Miszczyk, Keiichiro Miyajima et al.

2025 · 0 Zit.

Automated Classification of Adverse Events After Hydrogel Perirectal Spacer Insertion for Prostate Cancer Using Large Language Models

Nishan Sohoni, Nimit S. Sohoni, Ryan Sutherland et al.

2026 · 0 Zit.

Abstract PS3-04-06: Benchmarking Large Language Models for Clinical Decision Support in Breast Cancer Care: A Multi-Institutional Expert Evaluation

Z. Shah, S. S. Afridi, Mulham Ombada et al.

2026 · 0 Zit.

Federated deep learning enables cancer subtyping by proteomics

Zhaoxiang Cai, Emma L. Boys, Zainab Noor et al.

2024 · 0 Zit.

2619P How clinicians decide – analyzing real-world practice patterns in metastatic renal cell carcinoma (mRCC) with machine learning: Results from the international metastatic renal cell carcinoma database consortium (IMDC)

David Maj, D. O'Sullivan, Martín Zarbá et al.

2025 · 0 Zit.