Buchumschlag

Exploring Strategies for Personalized Radiation Therapy: Part III Identifying genetic determinants for Radiation Response with Meta Learning

Fuente: arXiv

Gespeichert in:

Bibliographische Detailangaben
Hauptverfasser:	Peng, Hao, Zhang, Yuanyuan, Jiang, Steve, Timmerman, Robert, Minna, John
Format:	Preprint
Veröffentlicht:	2025
Schlagworte:	Medical Physics Artificial Intelligence Machine Learning
Online-Zugang:	Acceder al recurso
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Ähnliche Einträge

Exploring Strategies for Personalized Radiation Therapy Part I Unlocking Response-Related Tumor Subregions with Class Activation Mapping
von: Peng, Hao, et al.
Veröffentlicht: (2025)

Exploring Strategies for Personalized Radiation Therapy Part II Predicting Tumor Drift Patterns with Diffusion Models
von: Peng, Hao, et al.
Veröffentlicht: (2025)

Exploring Strategies for Personalized Radiation Therapy Part IV: An Interaction-Picture Approach to Quantify the Abscopal Effect
von: Peng, Hao, et al.
Veröffentlicht: (2026)

Understanding the PULSAR Effect in Combined Radiotherapy and Immunotherapy through Attention Mechanisms with a Transformer Model
von: Peng, Hao, et al.
Veröffentlicht: (2024)

An Overview of the Development of Stereotactic Body Radiation Therapy
von: Zong, Yanqi, et al.
Veröffentlicht: (2024)

Towards Human-Centric Intelligent Treatment Planning for Radiation Therapy
von: Jafar, Adnan, et al.
Veröffentlicht: (2025)

Exploring the Capabilities and Limitations of Large Language Models for Radiation Oncology Decision Support
von: Putz, Florian, et al.
Veröffentlicht: (2025)

DosimeTron: Automating Personalized Monte Carlo Radiation Dosimetry in PET/CT with Agentic AI
von: Tzanis, Eleftherios, et al.
Veröffentlicht: (2026)

Large Language Model-Augmented Auto-Delineation of Treatment Target Volume in Radiation Therapy
von: Rajendran, Praveenbalaji, et al.
Veröffentlicht: (2024)

Fine-Tuning Open-Source Large Language Models to Improve Their Performance on Radiation Oncology Tasks: A Feasibility Study to Investigate Their Potential Clinical Applications in Radiation Oncology
von: Wang, Peilong, et al.
Veröffentlicht: (2025)

Evaluating The Performance of Using Large Language Models to Automate Summarization of CT Simulation Orders in Radiation Oncology
von: Cao, Meiyun, et al.
Veröffentlicht: (2025)

Integrated Transcriptomic-proteomic Biomarker Identification for Radiation Response Prediction in Non-small Cell Lung Cancer Cell Lines
von: Yu, Yajun, et al.
Veröffentlicht: (2025)

Paediatric Medical Imaging and Radiation Therapy
von: John Pearn
Veröffentlicht: (2026)

Automatic Personalized Impression Generation for PET Reports Using Large Language Models
von: Tie, Xin, et al.
Veröffentlicht: (2023)

An Optimization Framework to Personalize Passive Cardiac Mechanics
von: Shi, Lei, et al.
Veröffentlicht: (2024)

AI End-to-End Radiation Treatment Planning Under One Second
von: Arberet, Simon, et al.
Veröffentlicht: (2026)

Australian Society of Medical Imaging and Radiation Therapy Image Registration in Radiation Therapy Position Paper
von: Tamara Barry, et al.
Veröffentlicht: (2026)

Diffusion Transformer-based Universal Dose Denoising for Pencil Beam Scanning Proton Therapy
von: Ding, Yuzhen, et al.
Veröffentlicht: (2025)

Evaluation of a Novel Quantitative Multiparametric MR Sequence for Radiation Therapy Treatment Response Assessment
von: Yan, Yuhao, et al.
Veröffentlicht: (2025)

Continuing Professional Development – Radiation Therapy
Veröffentlicht: (2025)

Continuing Professional Development – Radiation Therapy
Veröffentlicht: (2026)

Continuing Professional Development—Radiation Therapy
Veröffentlicht: (2025)

Continuing Professional Development – Radiation Therapy
Veröffentlicht: (2024)

Continuing Professional Development – Radiation Therapy
Veröffentlicht: (2025)

Continuing Professional Development—Radiation Therapy
Veröffentlicht: (2025)

Continuing Professional Development ‐ Radiation Therapy
Veröffentlicht: (2024)

Continuing Professional Development ‐ Radiation Therapy
Veröffentlicht: (2024)

Continuing Professional Development ‐ Radiation Therapy
Veröffentlicht: (2024)

Continuing Professional Development ‐ Radiation Therapy
Veröffentlicht: (2024)

Continuing Professional Development ‐ Radiation Therapy
Veröffentlicht: (2024)

Review: Adaptive Radiation Therapy for Head and Neck Cancer
von: McCullum, Lucas, et al.
Veröffentlicht: (2025)

Microdosimetry Aspects in Diffusing Alpha-emitters Radiation Therapy. Part I: Effect of Broad Nucleus Size Distributions
von: Korotinsky, Yevgeniya, et al.
Veröffentlicht: (2025)

Dose-LET Interactions Predict Capsular Contracture After Proton Postmastectomy Radiation Therapy
von: Chen, Jingyuan, et al.
Veröffentlicht: (2026)

Multiomics-based Outcome Prediction for the Treatment of Brain Metastases with Personalized Ultra-fractionated Stereotactic Adaptive Radiotherapy (PULSAR)
von: Zhang, Haozhao, et al.
Veröffentlicht: (2024)

The Role of Artificial Intelligence in Enhancing Insulin Recommendations and Therapy Outcomes
von: Panagiotou, Maria, et al.
Veröffentlicht: (2025)

Leveraging Compressed Sensing and Radiomics for Robust Feature Selection for Outcome Prediction in Personalized Ultra‐Fractionated Stereotactic Adaptive Radiotherapy
von: Yajun Yu, et al.
Veröffentlicht: (2025)

Unsupervised Learning for Inverse Problems in Computed Tomography
von: Hellwege, Laura, et al.
Veröffentlicht: (2025)

Ultrasound-Guided Real-Time Spinal Motion Visualization for Spinal Instability Assessment
von: Li, Feng, et al.
Veröffentlicht: (2026)

Physics-Guided Radiotherapy Treatment Planning with Deep Learning
von: Achlatis, Stefanos, et al.
Veröffentlicht: (2025)

Referenceless Proton Resonance Frequency Thermometry Using Deep Learning with Self-Attention
von: Zhao, Yueran, et al.
Veröffentlicht: (2025)