32 citations · 83 across the 12 of their papers we have counts for
12 papers
Exploring the Capabilities and Limitations of Large Language Models for Radiation Oncology Decision Support
Florian Putz, Marlen Haderleina, Sebastian Lettmaier +3
Thanks to the rapidly evolving integration of LLMs into decision-support tools, a significant transformation is happening across large-scale systems. Like other medical fields, the…
Task-Specific Data Preparation for Deep Learning to Reconstruct Structures of Interest from Severely Truncated CBCT Data
Yixing Huang, Fuxin Fan, Ahmed Gomaa +4
Cone-beam computed tomography (CBCT) is widely used in interventional surgeries and radiation oncology. Due to the limited size of flat-panel detectors, anatomical structures might…
Fine-Tuning a Local LLaMA-3 Large Language Model for Automated Privacy-Preserving Physician Letter Generation in Radiation Oncology
Yihao Hou, Christoph Bert, Ahmed Gomaa +12
Generating physician letters is a time-consuming task in daily clinical practice. This study investigates local fine-tuning of large language models (LLMs), specifically LLaMA mode…
Multicenter Privacy-Preserving Model Training for Deep Learning Brain Metastases Autosegmentation
Yixing Huang, Zahra Khodabakhshi, Ahmed Gomaa +7
Objectives: This work aims to explore the impact of multicenter data heterogeneity on deep learning brain metastases (BM) autosegmentation performance, and assess the efficacy of a…
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…
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…
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…
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…
Risk Classification of Brain Metastases via Radiomics, Delta-Radiomics and Machine Learning
Philipp Sommer, Yixing Huang, Christoph Bert +5
Stereotactic radiotherapy (SRT) is one of the most important treatment for patients with brain metastases (BM). Conventionally, following SRT patients are monitored by serial imagi…
Deep learning for automatic head and neck lymph node level delineation provides expert-level accuracy
Thomas Weissmann, Yixing Huang, Stefan Fischer +16
Background: Deep learning (DL)-based head and neck lymph node level (HN_LNL) autodelineation is of high relevance to radiotherapy research and clinical treatment planning but still…
Continual Learning for Peer-to-Peer Federated Learning: A Study on Automated Brain Metastasis Identification
Yixing Huang, Christoph Bert, Stefan Fischer +5
Due to data privacy constraints, data sharing among multiple centers is restricted. Continual learning, as one approach to peer-to-peer federated learning, can promote multicenter…
Learning Perspective Deformation in X-Ray Transmission Imaging
Yixing Huang, Andreas Maier, Fuxin Fan +5
In cone-beam X-ray transmission imaging, perspective deformation causes difficulty in direct, accurate geometric assessments of anatomical structures. In this work, the perspective…