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20232026
most citedMulticenter Privacy-Preserving Model Training for Deep Learning Brain Metastases Autosegmentation

13 citations · 42 across the 13 of their papers we have counts for

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Showing 2023Show all

4 papers · 1 filter

cs.LG2023★ 1 cited

A Survey of Incremental Transfer Learning: Combining Peer-to-Peer Federated Learning and Domain Incremental Learning for Multicenter Collaboration

Yixing Huang, Christoph Bert, Ahmed Gomaa +3

Due to data privacy constraints, data sharing among multiple clinical centers is restricted, which impedes the development of high performance deep learning models from multicenter…

eess.IV2023

Deep Learning for Cancer Prognosis Prediction Using Portrait Photos by StyleGAN Embedding

Amr Hagag, Ahmed Gomaa, Dominik Kornek +5

Survival prediction for cancer patients is critical for optimal treatment selection and patient management. Current patient survival prediction methods typically extract survival i…

eess.IV2023★ 3 cited

The Segment Anything foundation model achieves favorable brain tumor autosegmentation accuracy on MRI to support radiotherapy treatment planning

Florian Putz, Johanna Grigo, Thomas Weissmann +13

Background: Tumor segmentation in MRI is crucial in radiotherapy (RT) treatment planning for brain tumor patients. Segment anything (SA), a novel promptable foundation model for au…

physics.med-ph2023★ 9 cited

Benchmarking ChatGPT-4 on ACR Radiation Oncology In-Training (TXIT) Exam and Red Journal Gray Zone Cases: Potentials and Challenges for AI-Assisted Medical Education and Decision Making in Radiation Oncology

Yixing Huang, Ahmed Gomaa, Sabine Semrau +12

The potential of large language models in medicine for education and decision making purposes has been demonstrated as they achieve decent scores on medical exams such as the Unite…