Cem Dede

Publications

• RNA2DNAlign: Nucleotide resolution allele asymmetries through quantitative assessment of RNA and DNA paired sequencing data
• Allele-Specific Gene Expression Analysis In Patients With Invasive Breast Carcinoma
• Identification of TRIM24 Domain Essentiality in Primary TRIM24COE Carcinosarcoma Cell Lines
• Development of a High-Performance Multiparametric MRI Oropharyngeal Primary Tumor Auto-Segmentation Deep Learning Model and Investigation of Input Channel Effects: Results from a Prospective Imaging Registry
• Evaluation of deep learning-based multiparametric MRI oropharyngeal primary tumor auto-segmentation and investigation of input channel effects: Results from a prospective imaging registry
• Head and Neck Cancer Primary Tumor Auto Segmentation using Model Ensembling of Deep Learning in PET-CT Images
• Progression Free Survival Prediction for Head and Neck Cancer using Deep Learning based on Clinical and PET-CT Imaging Data
• Combining Tumor Segmentation Masks with PET/CT Images and Clinical Data in a Deep Learning Framework for Improved Prognostic Prediction in Head and Neck Squamous Cell Carcinoma
• Quality Assurance Assessment of Diffusion-Weighted and T2-Weighted Magnetic Resonance Imaging Registration and Contour Propagation for Head and Neck Cancer Radiotherapy
• Deep Learning Auto-Segmentation of Cervical Neck Skeletal Muscle for Sarcopenia Analysis Using Pre-Therapy CT in Patients with Head and Neck Cancer
• Sub-Acute Post-Treatment Dysphagia and Shortness of Breath Symptoms Associate With Worse Survival in Oropharyngeal Cancer.
• Muscle and Adipose Tissue Segmentations at the C3 Vertebral Level for Sarcopenia-Related Clinical Decision-Making in Patients with Head and Neck Cancer
• Head and Neck Cancer Primary Tumor Auto Segmentation Using Model Ensembling of Deep Learning in PET/CT Images
• Progression Free Survival Prediction for Head and Neck Cancer Using Deep Learning Based on Clinical and PET/CT Imaging Data
• Quality Assurance Assessment of Intra-Acquisition Diffusion-Weighted and T2-Weighted Magnetic Resonance Imaging Registration and Contour Propagation for Head and Neck Cancer Radiotherapy
• Improved Xerostomia Prediction in Head and Neck Cancer Patients with Dixon Magnetic Resonance Imaging of Glandular Adiposity: Validation of Semi-Quantitative Parotid T1 Signal Intensity Metrics for Biomarker Pre-Qualification.
• Improved Xerostomia Prediction in Head and Neck Cancer Patients with Dixon Magnetic Resonance Imaging of Glandular Adiposity: Validation of Semi-Quantitative Parotid T1 Signal Intensity Metrics for Biomarker Pre-Qualification
• Sub-acute post-treatment dysphagia and shortness-of-breath symptom severity associates with survival and disease control in oropharyngeal cancer patients
• Dysphagia and shortness-of-breath as markers for treatment failure and survival in oropharyngeal cancer after radiation
• Personalized Rescheduling of Adaptive Organ-at-Risk-Sparing Radiation Therapy for Head and Neck Cancer under Re-planning Resource Constraints: A Novel Application of Markov Decision Processes
• Markov models for clinical decision‐making in radiation oncology: A systematic review
• International Multi-Specialty Expert Physician Preoperative Identification of Extranodal Extension in Oropharyngeal Cancer Patients using Computed Tomography: Prospective Blinded Human Inter-Observer Performance Evaluation.
• Markov models for clinical decision-making in radiation oncology: A systematic review
• Temporal characterization of acute pain and toxicity kinetics during radiation therapy for head and neck cancer. A retrospective study
• Deep learning auto-segmentation of cervical skeletal muscle for sarcopenia analysis in patients with head and neck cancer
• Cluster-Based Toxicity Estimation of Osteoradionecrosis Via Unsupervised Machine Learning: Moving Beyond Single Dose-Parameter Normal Tissue Complication Probability by Using Whole Dose-Volume Histograms for Cohort Risk Stratification
• Muscle and adipose tissue segmentations at the third cervical vertebral level in patients with head and neck cancer
• Cluster-Based Toxicity Estimation of Osteoradionecrosis via Unsupervised Machine Learning: Moving Beyond Single Dose-Parameter Normal Tissue Complication Probability by Using Whole Dose-Volume Histograms for Cohort Risk Stratification
• Quality assurance assessment of intra-acquisition diffusion-weighted and T2-weighted magnetic resonance imaging registration and contour propagation for head and neck cancer radiotherapy
• Computed tomography radiomics-based cross-sectional detection of mandibular osteoradionecrosis in head and neck cancer survivors
• Evaluating Observer Reliability and Diagnostic Accuracy of CT-LEFAT Criteria for Post-Treatment Head and Neck Lymphedema: A Prospective Blinded Comparative Analysis of Oncologist Human Inter-Rater Performance
• Cost-Effectiveness of Personalized Policies for Implementing Organ-at-Risk Sparing Adaptive Radiation Therapy in Head and Neck Cancer: A Markov Decision Process Approach
• Optimal timing of organs-at-risk-sparing adaptive radiation therapy for head-and-neck cancer under re-planning resource constraints
• Radiographic classification of mandibular osteoradionecrosis: A blinded prospective multi-disciplinary interobserver diagnostic performance study
• Overview of the Head and Neck Tumor Segmentation for Magnetic Resonance Guided Applications (HNTS-MRG) 2024 Challenge
• Technical Optimization of SyntheticMR for the Head and Neck on a 3T MR-Simulator and 1.5T MR-Linac: A Prospective R-IDEAL Stage 2a Technology Innovation Report