Five-year experience with setup and implementation of an integrated database system for clinical documentation and research. - Kerstin A. Kessel; Christian Bohn; Uwe Engelmann; Dieter Oetzel; Nina Bougatf; Rolf Bendl; Jürgen Debus; Stephanie E. Combs (Comput. Methods Programs Biomed., 2014)

Personalized Radiotherapy Planning for Glioma Using Multimodal Bayesian Model Calibration. - Jana Lipková; Panagiotis Angelikopoulos; Stephen Wu 001; Esther Alberts; Benedikt Wiestler; Christian Diehl; Christine Preibisch; Thomas Pyka; Stephanie Combs; Panagiotis E. Hadjidoukas; Koen Van Leemput; Petros Koumoutsakos; et al. (CoRR, 2018)

Shape-Aware Complementary-Task Learning for Multi-organ Segmentation. - Fernando Navarro; Suprosanna Shit; Ivan Ezhov; Johannes C. Paetzold; Andrei Gafita; Jan C. Peeken; Stephanie E. Combs; Bjoern H. Menze (MLMI@MICCAI, 2019)

Neighborhood Watch: Representation Learning with Local-Margin Triplet Loss and Sampling Strategy for K-Nearest-Neighbor Image Classification. - Phawis Thammasorn; Daniel S. Hippe; Wanpracha Art Chaovalitwongse; Matthew Spraker; Landon Wootton; Matthew Nyflot; Stephanie Combs; Jan Peeken; Eric Ford (CoRR, 2019)

Personalized Radiotherapy Design for Glioblastoma: Integrating Mathematical Tumor Models, Multimodal Scans, and Bayesian Inference. - Jana Lipková; Panagiotis Angelikopoulos; Stephen Wu 001; Esther Alberts; Benedikt Wiestler; Christian Diehl; Christine Preibisch; Thomas Pyka; Stephanie Combs; Panagiotis E. Hadjidoukas; Koen Van Leemput; Petros Koumoutsakos; et al. (IEEE Trans. Medical Imaging, 2019)

Deep Reinforcement Learning for Organ Localization in CT. - Fernando Navarro; Anjany Sekuboyina; Diana Waldmannstetter; Jan C. Peeken; Stephanie E. Combs; Bjoern H. Menze (MIDL, 2020)

Deep Learning Based HPV Status Prediction for Oropharyngeal Cancer Patients. - Daniel M. Lang 003; Jan C. Peeken; Stephanie E. Combs; Jan J. Wilkens; Stefan Bartzsch (CoRR, 2020)

2D and 3D convolutional neural networks for outcome modelling of locally advanced head and neck squamous cell carcinoma. - Sebastian Starke; Stefan Leger; Alex Zwanenburg; Karoline Leger; Fabian Lohaus; Annett Linge; Andreas Schreiber; Goda Kalinauskaite; Inge Tinhofer; Nika Guberina; Maja Guberina; Panagiotis Balermpas; et al. (RODARE, 2020)

A Video Data Based Transfer Learning Approach for Classification of MGMT Status in Brain Tumor MR Images. - Daniel M. Lang 003; Jan C. Peeken; Stephanie E. Combs; Jan J. Wilkens; Stefan Bartzsch (BrainLes@MICCAI (1), 2021)

Deep Learning Based GTV Delineation and Progression Free Survival Risk Score Prediction for Head and Neck Cancer Patients. - Daniel M. Lang 003; Jan C. Peeken; Stephanie E. Combs; Jan J. Wilkens; Stefan Bartzsch (HECKTOR@MICCAI, 2021)

Do We Need Complex Image Features to Personalize Treatment of Patients with Locally Advanced Rectal Cancer? - Iram Shahzadi; Annika Lattermann; Annett Linge; Alex Zwanenburg; Christian Baldus; Jan C. Peeken; Stephanie E. Combs; Michael Baumann 006; Mechthild Krause; Esther G. C. Troost; Steffen Löck (MICCAI (7), 2021)

Evaluating the Robustness of Self-Supervised Learning in Medical Imaging. - Fernando Navarro; Christopher Watanabe; Suprosanna Shit; Anjany Sekuboyina; Jan C. Peeken; Stephanie E. Combs; Bjoern H. Menze (CoRR, 2021)

A Unified 3D Framework for Organs-at-Risk Localization and Segmentation for Radiation Therapy Planning. - Fernando Navarro; Guido Sasahara; Suprosanna Shit; Anjany Sekuboyina; Ivan Ezhov; Jan C. Peeken; Stephanie E. Combs; Bjoern H. Menze (EMBC, 2022)

Self-Supervised Pretext Tasks in Model Robustness & Generalizability: A Revisit from Medical Imaging Perspective. - Fernando Navarro; Christopher Watanabe; Suprosanna Shit; Anjany Sekuboyina; Jan C. Peeken; Stephanie E. Combs; Bjoern H. Menze (EMBC, 2022)

Regularizing the Deepsurv Network Using Projection Loss for Medical Risk Assessment. - Phawis Thammasorn; Stephanie K. Schaub; Daniel S. Hippe; Matthew Spraker; Jan C. Peeken; Landon Wootton; Paul E. Kinahan; Stephanie E. Combs; Wanpracha Art Chaovalitwongse; Matthew Nyflot (IEEE Access, 2022)

A unified 3D framework for Organs at Risk Localization and Segmentation for Radiation Therapy Planning. - Fernando Navarro; Guido Sasahara; Suprosanna Shit; Ivan Ezhov; Jan C. Peeken; Stephanie E. Combs; Bjoern H. Menze (CoRR, 2022)

All Sizes Matter: Improving Volumetric Brain Segmentation on Small Lesions. - Ayhan Can Erdur; Daniel Scholz 005; Josef A. Buchner; Stephanie E. Combs; Daniel Rueckert; Jan C. Peeken (BraTS/CrossMoDA@MICCAI, 2023)

Nearest Neighbor-Based Strategy to Optimize Multi-View Triplet Network for Classification of Small-Sample Medical Imaging Data. - Phawis Thammasorn; Wanpracha Art Chaovalitwongse; Daniel S. Hippe; Landon Wootton; Eric Ford; Matthew Spraker; Stephanie E. Combs; Jan C. Peeken; Matthew Nyflot (IEEE Trans. Neural Networks Learn. Syst., 2023)

Data publication: Multitask learning with convolutional neural networks and vision transformers can improve outcome prediction for head and neck cancer patients. - Sebastian Starke; Alex Zwanenburg; Karoline Leger; Fabian Lohaus; Annett Linge; Andreas Schreiber; Goda Kalinauskaite; Inge Tinhofer; Nika Guberina; Maja Guberina; Panagiotis Balermpas; Jens von der Grün; et al. (RODARE, 2023)

Unifying Local and Global Shape Descriptors to Grade Soft-Tissue Sarcomas Using Graph Convolutional Networks. - Johannes Kiechle; Stefan M. Fischer; Daniel M. Lang 003; Maxime Di Folco; Sarah C. Foreman; Verena K. N. Rösner; Ann-Kathrin Lohse; Carolin Mogler; Carolin Knebel; Marcus R. Makowski; Klaus Woertler; Stephanie E. Combs; et al. (ISBI, 2024)

Analysis of clinical, dosimetric and radiomic features for predicting local failure after stereotactic radiotherapy of brain metastases in malignant melanoma. - Nanna E. Hartong; Ilias Sachpazidis; Oliver Blanck; Lucas Etzel; Jan C. Peeken; Stephanie E. Combs; Horst Urbach; Maxim Zaitsev; Dimos Baltas; Ilinca Popp; Anca-Ligia Grosu; Tobias Fechter (CoRR, 2024)

Improving Reliability and Explainability of Medical Question Answering through Atomic Fact Checking in Retrieval-Augmented LLMs. - Juraj Vladika; Annika Domres; Mai Nguyen; Rebecca Moser; Jana Nano; Felix Busch; Lisa C. Adams; Keno K. Bressem; Denise Bernhardt; Stephanie E. Combs; Kai J. Borm; Florian Matthes; et al. (CoRR, 2025)

CADS: A Comprehensive Anatomical Dataset and Segmentation for Whole-Body Anatomy in Computed Tomography. - Murong Xu; Tamaz Amiranashvili; Fernando Navarro; Maksym Fritsak; Ibrahim Ethem Hamamci; Suprosanna Shit; Bastian Wittmann; Sezgin Er; Sebastian M. Christ; Ezequiel de la Rosa; Julian Deseoe; Robert Graf; et al. (CoRR, 2025)